Genetic variants on chr 11q and 6q as markers for prostate and colorectal cancer predisposition

ABSTRACT

It has been discovered that certain polymorphic markers on chromosome 6 and chromosome 11 are indicative of a susceptibility to prostate cancer and colon cancer. The invention describes diagnostic applications for determining a susceptibility to cancer using such markers, as well as kits for use in such applications.

RELATED APPLICATION

This application claims priority under 35 U.S.C. §119 or 365 to Iceland, Application No. 8696, filed Nov. 30, 2007. The entire teachings of the above application are incorporated herein by reference.

BACKGROUND OF THE INVENTION

Cancer, the uncontrolled growth of malignant cells, is a major health problem of the modern medical era and is one of the leading causes of death in developed countries. In the United States, one in four deaths is caused by cancer (Jemal, A. et al., CA Cancer J. Clin. 52:23-47 (2002)).

The incidence of prostate cancer has dramatically increased over the last decades and prostate cancer is now a leading cause of death in the United States and Western Europe (Peschel, R. E. and J. W. Colberg, Lancet 4:233-41 (2003); Nelson, W. G. et al., N Engl. J. Med. 349(4):366-81 (2003)). Prostate cancer is the most frequently diagnosed noncutaneous malignancy among men in industrialized countries, and in the United States, 1 in 8 men will develop prostate cancer during his life (Simard, J. et al., Endocrinology 143(6):2029-40 (2002)). Although environmental factors, such as dietary factors and lifestyle-related factors, contribute to the risk of prostate cancer, genetic factors have also been shown to play an important role. Indeed, a positive family history is among the strongest epidemiological risk factors for prostate cancer, and twin studies comparing the concordant occurrence of prostate cancer in monozygotic twins have consistently revealed a stronger hereditary component in the risk of prostate cancer than in any other type of cancer (Nelson, W. G. et al., N. Engl. J. Med. 349(4):366-81 (2003); Lichtenstein P. et. al., N. Engl. J. Med. 343(2):78-85 (2000)). In addition, an increased risk of prostate cancer is seen in 1^(st) to 5^(th) degree relatives of prostate cancer cases in a nation wide study on the familiality of all cancer cases diagnosed in Iceland from 1955-2003 (Amundadottir et al., PLoS Medicine 1(3):e65 (2004)). The genetic basis for this disease, emphasized by the increased risk among relatives, is further supported by studies of prostate cancer among particular populations: for example, African Americans have among the highest incidence of prostate cancer and mortality rate attributable to this disease: they are 1.6 times as likely to develop prostate cancer and 2.4 times as likely to die from this disease than European Americans (Ries, L. A. G. et al., NIH Pub. No. 99-4649 (1999)).

An average 40% reduction in life expectancy affects males with prostate cancer. If detected early, prior to metastasis and local spread beyond the capsule, prostate cancer can be cured (e.g., using surgery). However, if diagnosed after spread and metastasis from the prostate, prostate cancer is typically a fatal disease with low cure rates. While prostate-specific antigen (PSA)-based screening has aided early diagnosis of prostate cancer, it is neither highly sensitive nor specific (Punglia et. al., N Engl J Med. 349(4):335-42 (2003)). This means that a high percentage of false negative and false positive diagnoses are associated with the test. The consequences are both many instances of missed cancers and unnecessary follow-up biopsies for those without cancer. As many as 65 to 85% of individuals (depending on age) with prostate cancer have a PSA value less than or equal to 4.0 ng/mL, which has traditionally been used as the upper limit for a normal PSA level (Punglia et. al., N Engl J Med. 349(4):335-42 (2003); Cookston, M. S., Cancer Control 8(2):133-40 (2001); Thompson, I. M. et. al., N Engl J Med. 350:2239-46 (2004)). A significant fraction of those cancers with low PSA levels are scored as Gleason grade 7 or higher, which is a measure of an aggressive prostate cancer.

In addition to the sensitivity problem outlined above, PSA testing also has difficulty with specificity and predicting prognosis. PSA levels can be abnormal in those without prostate cancer. For example, benign prostatic hyperplasia (BPH) is one common cause of a false-positive PSA test. In addition, a variety of noncancer conditions may elevate serum PSA levels, including urinary retention, prostatitis, vigorous prostate massage and ejaculation.

Subsequent confirmation of prostate cancer using needle biopsy in patients with positive PSA levels is difficult if the tumor is too small to see by ultrasound. Multiple random samples are typically taken but diagnosis of prostate cancer may be missed because of the sampling of only small amounts of tissue. Digital rectal examination (DRE) also misses many cancers because only the posterior lobe of the prostate is examined. As early cancers are nonpalpable, cancers detected by DRE may already have spread outside the prostate (Mistry K. J., Am. Board Fam. Pract. 16(2):95-101 (2003)).

Thus, there is clearly a great need for improved diagnostic procedures that would facilitate early-stage prostate cancer detection and prognosis, as well as aid in preventive and curative treatments of the disease. In addition, there is a need to develop tools to better identify those patients who are more likely to have aggressive forms of prostate cancer from those patients that are more likely to have more benign forms of prostate cancer that remain localized within the prostate and do not contribute significantly to morbidity or mortality. This would help to avoid invasive and costly procedures for patients not at significant risk.

The incidence of prostate cancer has dramatically increased over the last decades. Prostate cancer is a multifactorial disease with genetic and environmental components involved in its etiology. It is characterized by heterogeneous growth patterns that range from slow growing tumors to very rapid highly metastatic lesions.

Although genetic factors are among the strongest epidemiological risk factors for prostate cancer, the search for genetic determinants involved in the disease has been challenging. Studies have revealed that linking candidate genetic markers to prostate cancer has been more difficult than identifying susceptibility genes for other cancers, such as breast, ovary and colorectal cancer. Several reasons have been proposed for this increased difficulty including: the fact that prostate cancer is often diagnosed at a late age thereby often making it difficult to obtain DNA samples from living affected individuals for more than one generation; the presence within high-risk pedigrees of phenocopies that are associated with a lack of distinguishing features between hereditary and sporadic forms; and the genetic heterogeneity of prostate cancer and the accompanying difficulty of developing appropriate statistical transmission models for this complex disease (Simard, J. et al., Endocrinology 143(6):2029-40 (2002)).

Various genome scans for prostate cancer-susceptibility genes have been conducted and several prostate cancer susceptibility loci have been reported. For example, HPC1 (1q24-q25), PCAP (1q42-q43), HCPX (Xq27-q28), CAPB (1p36), HPC20 (20q13), HPC2/ELAC2 (17 μl) and 16q23 have been proposed as prostate cancer susceptibility loci (Simard, J. et al., Endocrinology 143(6):2029-40 (2002); Nwosu, V. et al., Hum. Mol. Genet. 10(20):2313-18 (2001)). In a genome scan conducted by Smith et al., the strongest evidence for linkage was at HPC1, although two-point analysis also revealed a LOD score of ≧1.5 at D4S430 and LOD scores ≧1.0 at several loci, including markers at Xq27-28 (Ostrander E. A. and J. L. Stanford, Am. J. Hum. Genet. 67:1367-75 (2000)). In other genome scans, two-point LOD scores of ≧1.5 for chromosomes 10q, 12q and 14q using an autosomal dominant model of inheritance, and chromosomes 1q, 8q, 10q and 16p using a recessive model of inheritance, have been reported, as well as nominal evidence for linkage to chr 2q, 12p, 15q, 16q and 16p. A genome scan for prostate cancer predisposition loci using a small set of Utah high risk prostate cancer pedigrees and a set of 300 polymorphic markers provided evidence for linkage to a locus on chromosome 17p (Simard, J. et al., Endocrinology 143(6):2029-40 (2002)). Eight new linkage analyses were published in late 2003, which depicted remarkable heterogeneity. Eleven peaks with LOD scores higher than 2.0 were reported, none of which overlapped (see Actane consortium, Schleutker et. al., Wiklund et. al., Witte et. al., Janer Xu et. al., Lange et. al., Cunningham et al.; all of which appear in Prostate, vol. 57 (2003)).

As described above, identification of particular genes involved in prostate cancer has been challenging. One gene that has been implicated is RNASEL, which encodes a widely expressed latent endoribonuclease that participates in an interferon-inducible RNA-decay pathway believed to degrade viral and cellular RNA, and has been linked to the HPC locus (Carpten, J. et al., Nat. Genet. 30:181-84 (2002); Casey, G. et al., Nat. Genet. 32(4):581-83 (2002)). Mutations in RNASEL have been associated with increased susceptibility to prostate cancer. For example, in one family, four brothers with prostate cancer carried a disabling mutation in RNASEL, while in another family, four of six brothers with prostate cancer carried a base substitution affecting the initiator methionine codon of RNASEL. Other studies have revealed mutant RNASEL alleles associated with an increased risk of prostate cancer in Finnish men with familial prostate cancer and an Ashkenazi Jewish population (Rokman, A. et al., Am J. Hum. Genet. 70:1299-1304 (2002); Rennert, H. et al., Am J. Hum. Genet. 71:981-84 (2002)). In addition, the Ser217Leu genotype has been proposed to account for approximately 9% of all sporadic cases in Caucasian Americans younger than 65 years (Stanford, J. L., Cancer Epidemiol. Biomarkers Prev. 12(9):876-81 (2003)). In contrast to these positive reports, however, some studies have failed to detect any association between RNASEL alleles with inactivating mutations and prostate cancer (Wang, L. et al., Am. J. Hum. Genet. 71:116-23 (2002); Wiklund, F. et al., Clin. Cancer Res. 10(21):7150-56 (2004); Maier, C. et. al., Br. J. Cancer 92(6):1159-64 (2005)).

The macrophage-scavenger receptor 1 (MSR1) gene, which is located at 8p22, has also been identified as a candidate prostate cancer-susceptibility gene (Xu, J. et al., Nat. Genet. 32:321-25 (2002)). A mutant MSR1 allele was detected in approximately 3% of men with nonhereditary prostate cancer but only 0.4% of unaffected men. However, not all subsequent reports have confirmed these initial findings (see, e.g., Lindmark, F. et al., Prostate 59(2):132-40 (2004); Seppala, E. H. et al., Clin. Cancer Res. 9(14):5252-56 (2003); Wang, L. et al., Nat Genet. 35(2):128-29 (2003); Miller, D. C. et al., Cancer Res. 63(13):3486-89 (2003)). MSR1 encodes subunits of a macrophage-scavenger receptor that is capable of binding a variety of ligands, including bacterial lipopolysaccharide and lipoteicholic acid, and oxidized high-density lipoprotein and low-density lipoprotein in serum (Nelson, W. G. et al., N. Engl. J. Med. 349(4):366-81 (2003)).

The ELAC2 gene on Chr17p was the first prostate cancer susceptibility gene to be cloned in high risk prostate cancer families from Utah (Tavtigian, S. V., et al., Nat. Genet. 27(2):172-80 (2001)). A frameshift mutation (1641InsG) was found in one pedigree. Three additional missense changes: Ser217Leu; Ala541Thr; and Arg781His, were also found to associate with an increased risk of prostate cancer. The relative risk of prostate cancer in men carrying both Ser217Leu and Ala541Thr was found to be 2.37 in a cohort not selected on the basis of family history of prostate cancer (Rebbeck, T. R., et al., Am. J. Hum. Genet. 67(4):1014-19 (2000)). Another study described a new termination mutation (Glu216X) in one high incidence prostate cancer family (Wang, L., et al., Cancer Res. 61(17):6494-99 (2001)). Other reports have not demonstrated strong association with the three missense mutations, and a recent metaanalysis suggests that the familial risk associated with these mutations is more moderate than was indicated in initial reports (Vesprini, D., et al., Am. J. Hum. Genet. 68(4):912-17 (2001); Shea, P. R., et al., Hum. Genet. 111(4-5):398-400 (2002); Suarez, B. K, et al., Cancer Res. 61(13):4982-84 (2001); Severi, G., et al., J. Natl. Cancer Inst. 95(11):818-24 (2003); Fujiwara, H., et al., J. Hum. Genet. 47(12):641-48 (2002); Camp, N. J., et al., Am. J. Hum. Genet. 71(6):1475-78 (2002)).

Polymorphic variants of genes involved in androgen action (e.g., the androgen receptor (AR) gene, the cytochrome P-450c17 (CYP17) gene, and the steroid-5-α-reductase type II (SRD5A2) gene), have also been implicated in increased risk of prostate cancer (Nelson, W. G. et al., N. Engl. J. Med. 349(4):366-81 (2003)). With respect to AR, which encodes the androgen receptor, several genetic epidemiological studies have shown a correlation between an increased risk of prostate cancer and the presence of short androgen-receptor polyglutamine repeats, while other studies have failed to detect such a correlation. Linkage data has also implicated an allelic form of CYP17, an enzyme that catalyzes key reactions in sex-steroid biosynthesis, with prostate cancer (Chang, B. et al., Int. J. Cancer 95:354-59 (2001)). Allelic variants of SRD5A2, which encodes the predominant isozyme of 5-α-reductase in the prostate and functions to convert testosterone to the more potent dihydrotestosterone, have been associated with an increased risk of prostate cancer and with a poor prognosis for men with prostate cancer (Makridakis, N. M. et al., Lancet 354:975-78 (1999); Nam, R. K. et al., Urology 57:199-204 (2001)).

In short, despite the effort of many groups around the world, the genes that account for a substantial fraction of prostate cancer risk have not been identified. Although twin studies have implied that genetic factors are likely to be prominent in prostate cancer, only a handful of genes have been identified as being associated with an increased risk for prostate cancer, and these genes account for only a low percentage of cases. Thus, it is clear that the majority of genetic risk factors for prostate cancer remain to be found. It is likely that these genetic risk factors will include a relatively high number of low-to-medium risk genetic variants. These low-to-medium risk genetic variants may, however, be responsible for a substantial fraction of prostate cancer, and their identification, therefore, a great benefit for public health. Furthermore, none of the published prostate cancer genes have been reported to predict a greater risk for aggressive prostate cancer than for less aggressive prostate cancer.

Extensive genealogical information for a population containing cancer patients has in a recent study been combined with powerful gene sharing methods to map a locus on chromosome 8q24.21, which has been demonstrated to play a major role in cancer. Various cancer patients and their relatives were genotyped with a genome-wide marker set including 1100 microsatellite markers, with an average marker density of 3-4 cM. (Amundadottir L. T., Nature Genet. 38(6):652-658 (2006)). Association was detected to a single LD block within the locus between positions 128.414 and 128.506 Mb (NCBI build 34) in Utah CEPH HapMap samples.

Colorectal Cancer (CRC) is one of the most commonly diagnosed cancers and one of the leading causes of cancer mortality (Parkin D M, et. al. CA Cancer J Clin, 55,:74-108 (2005)). Cancers of the colon and rectum accounted for about 1 million new cases in 2002 (9.4% of cancer cases world-wide) and it affects men and women almost equally. The average lifetime risk for an individual in the US to develop CRC is 6% (Jemal A, et al. CA Cancer J. Clin., 56:106-30 (2006)). The prognosis is strongly associated with the stage of the disease at diagnosis; therefore, CRC screening presents an opportunity for early cancer detection and cancer prevention.

Colorectal cancer is a consequence of environmental exposures acting upon a background of genetically determined susceptibility. Studies indicate that 30-35% of colorectal cancer risk could be explained by genetic factors (Lichtenstein P, et. al. N Engl J Med, 343:78-85 (2000);) Peto J and Mack T M. Nat Genet, 26:411-4 (2000); Risch N. Cancer Epidemiol Biomarkers Prev, 10:733-41 (2001)). The analysis of cancer occurrence in relatives of cancer patients also lends strong evidence for genetic factors that increase the risk of cancer.

At present only a small percentage of the heritable risk of CRC is identified, usually through the investigation of rare cancer syndromes. High-penetrance mutations in several genes have been identified in rare hereditary colorectal cancer syndromes. The most common of these are the familial adenomatous polyposis (FAP) syndrome and hereditary non-polyposis colorectal cancer (HNPCC) or Lynch syndrome (LS). FAP, caused by mutations in the APC gene, is an autosomal dominant syndrome, characterized by early onset of multiple adenomatous polyps in the colon that eventually progress to cancer. LS is caused by mutations in DNA mismatch repair (MMR) genes and is considered to be the most common hereditary CRC syndrome, comprising approximately 3-5% of all CRCs (de la Chapelle, A. Fam Cancer, 4:233-7 (2005)).

The search for additional highly-penetrant CRC genes has not been fruitful and accumulating evidence supports the notion that no single susceptibility gene is likely to explain a large proportion of highly familial or early onset CRC. This has led to the currently favored hypothesis that most of the inherited CRC risk is due to multiple, low genetic risk variants. Each such variant would be expected to carry a small increase in risk; however, if the variant is common, it may contribute significantly to the population attributable risk (PAR).

SUMMARY OF THE INVENTION

The present invention relates to the use of polymorphic markers in diagnostic methods, kits and apparatus for determining susceptibility to prostate cancer and colorectal cancer.

In one aspect, the present invention relates to a method for determining a susceptibility to a cancer selected from prostate cancer and colorectal cancer in a human individual, comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, or in a genotype dataset from the individual, wherein the at least one polymorphic marker is selected from markers selected from the group consisting of markers within LD Block C11 and LD Block C06, and wherein the presence of the at least one allele is indicative of a susceptibility to the cancer.

In another aspect, the present invention relates to a method for determining a susceptibility to a cancer selected from prostate cancer and colorectal cancer in a human individual, comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, or in a genotype dataset from the individual, wherein the at least one polymorphic marker is selected from the group consisting of the markers set forth in Table 5 and Table 6, and markers in linkage disequilibirium therewith, and wherein the presence of the at least one allele is indicative of a susceptibility to the cancer. Determining a susceptibility comprises in one embodiment a diagnosis of a susceptibility. Diagnosis may be made by a medical professional, or other professional that provides information about disease risk. Alternatively, diagnosis of a susceptibility is provided by a genotype provider, or by an individual or organization that interprets genotype data for an individual or groups of individuals.

The genotype dataset comprises in one embodiment information about marker identity and the allelic status of the individual for at least one allele of a marker, i.e. information about the identity of at least one allele of the marker in the individual. The genotype dataset may comprise allelic information (information about allelic status) about one or more marker, including two or more markers, three or more markers, five or more markers, ten or more markers, one hundred or more markers, an so on. In some embodiments, the genotype dataset comprises genotype information from a whole-genome assessment of the individual, that may include hundreds of thousands of markers, or even one million or more markers spanning the entire genome of the individual.

Another aspect relates to a method of determining a susceptibility to a cancer selected from prostate cancer and colorectal cancer in a human individual, comprising determining whether at least one at-risk allele in at least one polymorphic marker is present in a genotype dataset derived from the individual, wherein the at least one polymorphic marker is selected from the group consisting of the markers set forth in Tables 5 and 6, and markers in linkage disequilibrium therewith, and wherein determination of the presence of the at least one at-risk allele is indicative of increased susceptibility to cancer.

Another aspect of the invention relates to a method of determining a susceptibility to prostate cancer, the method comprising: obtaining nucleic acid sequence data about a human individual identifying at least one allele of at least one polymorphic marker, wherein different alleles of the at least one polymorphic marker are associated with different susceptibilities to prostate cancer in humans, and determining a susceptibility to prostate cancer from the nucleic acid sequence data, wherein the at least one polymorphic marker is selected from the group consisting of rs10896450, and markers in linkage disequilibirium therewith.

In general, polymorphic genetic markers lead to alternate sequences at the nucleic acid level. If the nucleic acid marker changes the codon of a polypeptide encoded by the nucleic acid, then the marker will also result in alternate sequence at the amino acid level of the encoded polypeptide (polypeptide markers). Determination of the identity of particular alleles at polymorphic markers in a nucleic acid or particular alleles at polypeptide markers comprises whether particular alleles are present at a certain position in the sequence. Sequence data identifying a particular allele at a marker comprises sufficient sequence to detect the particular allele. For single nucleotide polymorphisms (SNPs) or amino acid polymorphisms described herein, sequence data can comprise sequence at a single position, i.e. the identity of a nucleotide or amino acid at a single position within a sequence. The sequence data can optionally include information about sequence flanking the polymorphic site, which in the case of SNPs spans a single nucleotide.

In certain embodiments, it may be useful to determine the nucleic acid sequence for at least two polymorphic markers. In other embodiments, the nucleic acid sequence for at least three, at least four or at least five or more polymorphic markers is determined. Haplotype information can be derived from an analysis of two or more polymorphic markers. Thus, in certain embodiments, a further step is performed, whereby haplotype information is derived based on sequence data for at least two polymorphic markers.

The invention also provides a method of determining a susceptibility to a cancer selected from prostate cancer and colorectal cancer in a human individual, the method comprising obtaining nucleic acid sequence data about a human individual identifying both alleles of at least two polymorphic markers selected from the markers listed in Table 3 and Table 4, and markers in linkage disequilibrium therewith, determine the identity of at least one haplotype based on the sequence data, and determine a susceptibility to the cancer from the haplotype data.

In certain embodiments, determination of a susceptibility comprises comparing the nucleic acid sequence data to a database containing correlation data between the at least one polymorphic marker and susceptibility to cancer. In some embodiments, the database comprises at least one risk measure of susceptibility to cancer for the at least one marker. The sequence database can for example be provided as a look-up table that contains data that indicates the susceptibility of cancer for any one, or a plurality of, particular polymorphisms. The database may also contain data that indicates the susceptibility for a particular haplotype that comprises at least two polymorphic markers.

Obtaining nucleic acid sequence data can in certain embodiments comprise obtaining a biological sample from the human individual and analyzing sequence of the at least one polymorphic marker in nucleic acid in the sample. Analyzing sequence can comprise determining the presence or absence of at least one allele of the at least one polymorphic marker. Determination of the presence of a particular susceptibility allele (e.g., an at-risk allele) is indicative of susceptibility to cancer in the human individual. Determination of the absence of a particular susceptibility allele is indicative that the particular susceptibility due to the at least one polymorphism is not present in the individual.

In some embodiments, obtaining nucleic acid sequence data comprises obtaining nucleic acid sequence information from a preexisting record. The preexisting record can for example be a computer file or database containing sequence data, such as genotype data, for the human individual, for at least one polymorphic marker.

Susceptibility determined by the diagnostic methods of the invention can be reported to a particular entity. In some embodiments, the at least one entity is selected from the group consisting of the individual, a guardian of the individual, a genetic service provider, a physician, a medical organization, and a medical insurer.

In certain embodiments, genetic markers associated with risk of prostate cancer and/or colorectal cancer as described herein are indicative of different response rates to particular treatment modalities for the cancer. Thus, in certain embodiments, the presence of the marker or haplotype is indicative of a different response rate of the subject to a particular treatment modality.

Another aspect of the invention relates to a method of identification of a marker for use in assessing susceptibility to prostate cancer, the method comprising

identifying at least one polymorphic marker within LD Block C06 or LD Block C11, or at least one polymorphic marker in linkage disequilibrium therewith;

determining the genotype status of a sample of individuals diagnosed with, or having a susceptibility to, prostate cancer; and

determining the genotype status of a sample of control individuals;

wherein a significant difference in frequency of at least one allele in at least one polymorphism in individuals diagnosed with, or having a susceptibility to, prostate cancer, as compared with the frequency of the at least one allele in the control sample is indicative of the at least one polymorphism being useful for assessing susceptibility to prostate cancer.

The invention also relates, in another aspect, to a method of identification of a marker for use in assessing susceptibility to colorectal cancer, the method comprising

identifying at least one polymorphic marker within The LD Block C11 genomic region, or at least one polymorphic marker in linkage disequilibrium therewith;

determining the genotype status of a sample of individuals diagnosed with, or having a susceptibility to, colorectal cancer; and

determining the genotype status of a sample of control individuals;

wherein a significant difference in frequency of at least one allele in at least one polymorphism in individuals diagnosed with, or having a susceptibility to, colorectal cancer, as compared with the frequency of the at least one allele in the control sample is indicative of the at least one polymorphism being useful for assessing susceptibility to colorectal cancer. In one embodiment, an increase in frequency of the at least one allele in the at least one polymorphism in individuals diagnosed with, or having a susceptibility to, the cancer, as compared with the frequency of the at least one allele in the control sample is indicative of the at least one polymorphism being useful for assessing increased susceptibility to the cancer. In another embodiment, a decrease in frequency of the at least one allele in the at least one polymorphism in individuals diagnosed with, or having a susceptibility to, the cancer, as compared with the frequency of the at least one allele in the control sample is indicative of the at least one polymorphism being useful for assessing decreased susceptibility to, or protection against, the cancer.

The invention, in another aspect, also relates to a method of genotyping a nucleic acid sample obtained from a human individual at risk for, or diagnosed with, a cancer selected from prostate cancer and colorectal cancer, comprising determining the presence or absence of at least one allele of at least one polymorphic marker in the sample, wherein the at least one marker is selected from the markers set forth in Table 3 and Table 4, and markers in linkage disequilibrium therewith, and wherein the presence of the at least one allele is indicative of a susceptibility to the cancer. In one embodiment, genotyping comprises amplifying a segment of a nucleic acid that comprises the at least one polymorphic marker by Polymerase Chain Reaction (PCR), using a nucleotide primer pair flanking the at least one polymorphic marker. In another embodiment, genotyping is performed using a process selected from allele-specific probe hybridization, allele-specific primer extension, allele-specific amplification, nucleic acid sequencing, 5′-exonuclease digestion, molecular beacon assay, oligonucleotide ligation assay, size analysis, and single-stranded conformation analysis. In one preferred embodiment, the process comprises allele-specific probe hybridization. In another preferred embodiment, the process comprises DNA sequencing. In yet another preferred embodiment, genotyping comprises the steps of

contacting copies of the nucleic acid with a detection oligonucleotide probe and an enhancer oligonucleotide probe under conditions for specific hybridization of the oligonucleotide probe with the nucleic acid;

wherein

the detection oligonucleotide probe is from 5-100 nucleotides in length and specifically hybridizes to a first segment of the nucleic acid whose nucleotide sequence is given by SEQ ID NO:2 that comprises at least one polymorphic site;

the detection oligonucleotide probe comprises a detectable label at its 3′ terminus and a quenching moiety at its 5′ terminus;

the enhancer oligonucleotide is from 5-100 nucleotides in length and is complementary to a second segment of the nucleotide sequence that is 5′ relative to the oligonucleotide probe, such that the enhancer oligonucleotide is located 3′ relative to the detection oligonucleotide probe when both oligonucleotides are hybridized to the nucleic acid; and

a single base gap exists between the first segment and the second segment, such that when the oligonucleotide probe and the enhancer oligonucleotide probe are both hybridized to the nucleic acid, a single base gap exists between the oligonucleotides;

treating the nucleic acid with an endonuclease that will cleave the detectable label from the 3′ terminus of the detection probe to release free detectable label when the detection probe is hybridized to the nucleic acid; and

measuring free detectable label, wherein the presence of the free detectable label indicates that the detection probe specifically hybridizes to the first segment of the nucleic acid, and indicates the sequence of the polymorphic site as the complement of the detection probe. The copies of the nucleic acid are preferably provided by amplification by Polymerase Chain Reaction (PCR).

Another aspect relates to a method of assessing an individual for probability of response to a therapeutic agent for preventing and/or ameliorating symptoms associated with cancer, comprising: determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, wherein the at least one polymorphic marker is selected from the group consisting of the polymorphic markers set forth in Table 3 and Table 4, and markers in linkage disequilibrium therewith, wherein the presence of the at least one allele of the at least one marker is indicative of a probability of a positive response to a cancer therapeutic agent.

Another aspect relates to a method of predicting prognosis of an individual diagnosed with a cancer selected from prostate cancer and colorectal cancer, the method comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, wherein the at least one polymorphic marker is selected from the group consisting of the polymorphic markers listed in Table 3 and Table 4, and markers in linkage disequilibrium therewith, wherein the presence of the at least one allele is indicative of a worse prognosis of the cancer in the individual.

Yet another aspect relates to a method of monitoring progress of a treatment of an individual undergoing treatment for a cancer selected from prostate cancer and colorectal cancer, the method comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, wherein the at least one polymorphic marker is selected from the group consisting of the polymorphic markers listed in Table 3 and Table 4, and markers in linkage disequilibrium therewith, wherein the presence of the at least one allele is indicative of the treatment outcome of the individual.

The invention in another aspect relates to a kit for assessing susceptibility to a cancer selected from prostate cancer and colorectal cancer in a human individual, the kit comprising reagents for selectively detecting at least one allele of at least one polymorphic marker in the genome of the individual, wherein the polymorphic marker is selected from the group consisting of the polymorphic markers set forth in Table 5 and Table 6, and markers in linkage disequilibrium therewith, and a collection of data comprising correlation data between the polymorphic markers assessed by the kit and susceptibility to prostate cancer and/or colorectal cancer. In one embodiment, the reagents comprise at least one contiguous oligonucleotide that hybridizes to a fragment of the genome of the individual comprising the at least one polymorphic marker, a buffer and a detectable label. In another embodiment, the reagents comprise at least one pair of oligonucleotides that hybridize to opposite strands of a genomic nucleic acid segment obtained from the subject, wherein each oligonucleotide primer pair is designed to selectively amplify a fragment of the genome of the individual that includes one polymorphic marker, and wherein the fragment is at least 30 base pairs in size. In yet another embodiment, the at least one oligonucleotide is completely complementary to the genome of the individual. In one embodiment, the oligonucleotide is about 18 to about 50 nucleotides in length. In another embodiment, the oligonucleotide is 20-30 nucleotides in length.

In one preferred embodiment, the kit comprises:

a detection oligonucleotide probe that is from 5-100 nucleotides in length;

an enhancer oligonucleotide probe that is from 5-100 nucleotides in length; and

an endonuclease enzyme;

wherein the detection oligonucleotide probe specifically hybridizes to a first segment of the nucleic acid whose nucleotide sequence is given by SEQ ID NO: 201 that comprises at least one polymorphic site; and

wherein the detection oligonucleotide probe comprises a detectable label at its 3′ terminus and a quenching moiety at its 5′ terminus;

wherein the enhancer oligonucleotide is from 5-100 nucleotides in length and is complementary to a second segment of the nucleotide sequence that is 5′ relative to the oligonucleotide probe, such that the enhancer oligonucleotide is located 3′ relative to the detection oligonucleotide probe when both oligonucleotides are hybridized to the nucleic acid;

wherein a single base gap exists between the first segment and the second segment, such that when the oligonucleotide probe and the enhancer oligonucleotide probe are both hybridized to the nucleic acid, a single base gap exists between the oligonucleotides; and

wherein treating the nucleic acid with the endonuclease will cleave the detectable label from the 3′ terminus of the detection probe to release free detectable label when the detection probe is hybridized to the nucleic acid.

Another aspect of the invention relates to the use of an oligonucleotide probe in the manufacture of a diagnostic reagent for diagnosing and/or assessing susceptibility to a cancer selected from prostate cancer and colorectal cancer in a human individual, wherein the probe hybridizes to a segment of a nucleic acid within LD Block C06 or LD Block C11 that comprises at least one polymorphic site, wherein the fragment is 15-500 nucleotides in length.

The invention also provides computer-implemented aspects. In one such aspect, the invention provides a computer-readable medium having computer executable instructions for determining susceptibility to a cancer selected from prostate cancer and colorectal cancer in an individual, the computer readable medium comprising: data representing at least one polymorphic marker; and a routine stored on the computer readable medium and adapted to be executed by a processor to determine susceptibility to the cancer in an individual based on the allelic status of at least one allele of said at least one polymorphic marker in the individual.

In one embodiment, said data representing at least one polymorphic marker comprises at least one parameter indicative of the susceptibility to the cancer linked to said at least one polymorphic marker. In another embodiment, said data representing at least one polymorphic marker comprises data indicative of the allelic status of at least one allele of said at least one allelic marker in said individual. In another embodiment, said routine is adapted to receive input data indicative of the allelic status for at least one allele of said at least one allelic marker in said individual. In a preferred embodiment, the at least one marker is selected from rs10896450 and rs10943605, and markers in linkage disequilibrium therewith. In another preferred embodiment, the at least one polymorphic marker is selected from the markers set forth in Table 3 and Table 4.

The invention further provides an apparatus for determining a genetic indicator for a cancer selected from prostate cancer and colorectal cancer in a human individual, comprising:

a processor,

a computer readable memory having computer executable instructions adapted to be executed on the processor to analyze marker and/or haplotype information for at least one human individual with respect to a cancer selected from prostate cancer and colorectal cancer, and

generate an output based on the marker or haplotype information, wherein the output comprises a risk measure of the at least one marker or haplotype as a genetic indicator of the cancer for the human individual.

In one embodiment, the computer readable memory comprises data indicative of the frequency of at least one allele of at least one polymorphic marker or at least one haplotype in a plurality of individuals diagnosed with prostate cancer and/or colorectal cancer, and data indicative of the frequency of at the least one allele of at least one polymorphic marker or at least one haplotype in a plurality of reference individuals, and wherein a risk measure is based on a comparison of the at least one marker and/or haplotype status for the human individual to the data indicative of the frequency of the at least one marker and/or haplotype information for the plurality of individuals diagnosed with the cancer. In one embodiment, the computer readable memory further comprises data indicative of a risk of developing prostate cancer and/or colorectal cancer associated with at least one allele of at least one polymorphic marker or at least one haplotype, and wherein a risk measure for the human individual is based on a comparison of the at least one marker and/or haplotype status for the human individual to the risk associated with the at least one allele of the at least one polymorphic marker or the at least one haplotype. In another embodiment, the computer readable memory further comprises data indicative of the frequency of at least one allele of at least one polymorphic marker or at least one haplotype in a plurality of individuals diagnosed with a cancer selected from prostate cancer and colorectal cancer, and data indicative of the frequency of at the least one allele of at least one polymorphic marker or at least one haplotype in a plurality of reference individuals, and wherein risk of developing the cancer is based on a comparison of the frequency of the at least one allele or haplotype in individuals diagnosed with the cancer, and reference individuals. In a preferred embodiment, the at least one marker is selected from rs10943605 and rs10896450, and markers in linkage disequilibrium therewith. In another preferred embodiment, the at least one polymorphic marker is selected from the markers set forth in Table 3 and Table 4.

Different embodiments of the various aspects of the invention relate to specific use of the polymorphic variants described herein to be associated with prostate cancer and colorectal cancer, or variants (polymorphic markers) in linkage disequilibrium therewith. In one embodiment of the invention, the at least one marker is selected from the markers within LD Block C06 and/or LD Block C11, as defined herein, and markers in linkage disequilibrium therewith. In one such embodiment, the at least one marker is selected from markers within LD Block C06 and/or LD Block C11. In one embodiment, the at least one polymorphic marker is selected from the markers set forth in Table 5 and Table 6. In another embodiment, the at least one polymorphic marker comprises at least one marker selected from the group of markers set forth in Table 3 and Table 4, and markers in linkage disequilibrium therewith. One embodiment relates to at least one marker selected from the group consisting of marker rs10896450, marker rs11228565, marker rs7947353 and marker rs10943605, and markers in linkage disequilibrium therewith. One embodiment relates to marker rs10896450, and markers in linkage disequilibrium therewith. One embodiment relates to marker rs11228565, and markers in linkage disequilibrium therewith. One embodiment relates to marker rs10943605, and markers in linkage disequilibrium therewith. One embodiment relates to marker rs10896450. Another embodiment relates to marker rs11228565. Another embodiment relates to marker rs10943605. In certain embodiments, the cancer assessed by the invention is prostate cancer. In certain other embodiments, the cancer is colorectal cancer. In one such embodiment, the at least one polymorphic marker is selected from the group of markers set forth in Table 3. In another embodiment, the marker is rs10943605, and markers in linkage disequilibrium therewith.

Some embodiments of the invention, further comprise assessing the frequency of at least one haplotype in the individual.

The methods of the invention comprise, in some embodiments, an additional step of assessing at least one biomarker in a sample from the individual. The sample can be a blood sample or a cancer biopsy sample, or any other biological sample derived from an individual that is suitable for assessing the presence or absence, or for quantitative determination, of at least one biomarker. The biomarker is preferably a biological molecule that represents directly or indirectly the disease state in question, i.e. prostate cancer or colorectal cancer. An exemplary biomarker is PSA. Other embodiments of the methods of the invention further comprise analyzing non-genetic information to make risk assessment, diagnosis, or prognosis of the individual. The non-genetic information is in some embodiments selected from age, gender, ethnicity, socioeconomic status, previous disease diagnosis, medical history of subject, family history of cancer, biochemical measurements, and clinical measurements.

Other genetic risk factors for cancer, e.g., prostate cancer and/or colorectal cancer, can be assessed in combination with the markers of the present invention found to be predictive of these cancers, for providing overall risk assessment of prostate cancer and/or colorectal cancer. Thus, in one embodiment, the methods of the invention relate to further steps comprising assessing the presence of absence of at least one additional genetic risk factor for prostate cancer or colorectal cancer in the individual. In certain embodiments, the additional genetic risk factor is not associated, defined by values of r² of at least 0.2 and/or values of |D′| of at least 0.8, to markers set forth in Tables 3 and 4, in particular marker rs10896450, marker rs11228565, marker rs7947353 and marker rs10943605. Such additional risk factor are in certain embodiments risk factors for a particular type of cancer, i.e. cancer at a particular site (e.g., prostate cancer and/or colorectal cancer). In certain other embodiments, such additional risk factors are susceptibility variants for multiple forms of cancer.

Thus, in certain embodiments, a further step is included, comprising determining whether at least one at-risk allele of at least one at-risk variant for a cancer selected from prostate cancer and colorectal cancer not in linkage disequilibrium with any one of the markers rs10896450, rs11228565, rs7947353 and rs10943605 are present in a sample comprising genomic DNA from a human individual or a genotype dataset derived from a human individual. In other words, genetic markers in other locations in the genome can be useful in combination with the markers of the present invention, so as to determine overall risk of the cancer based on multiple genetic variants. In one embodiment, the at least one at-risk variant for cancer is not in linkage disequilibrium with marker rs10896450. Selection of markers that are not in linkage disequilibrium (not in LD) can be based on a suitable measure for linkage disequilibrium, as described further herein. In certain embodiments, markers that are not in linkage disequilibrium have values for the LD measure r² correlating the markers of less than 0.2. In certain other embodiments, markers that are not in LD have values for r² correlating the markers of less than 0.15, including less than 0.10, less than 0.05, less than 0.02 and less than 0.01. Other suitable numerical values for establishing that markers are not in LD are contemplated, including values bridging any of the above-mentioned values.

The risk factors are in one embodiment selected from rs1447295, rs4430796, rs1859962, rs5945572, rs6983267, rs16901979 and rs10505483, and markers in linkage disequilibrium therewith. In another embodiment, the additional genetic risk factor is selected from the group consisting of rs2710646 allele A, rs16901979 allele A, rs1447295 allele A, rs6983267 allele G, rs10896450 allele G, rs1859962 allele G, rs4430796 allele A and rs5945572 allele A. In other embodiments, the additional genetic risk factor is selected from markers in linkage disequilibrium with any of the markers rs2710646, rs16901979, rs1447295, rs6983267, rs10896450, rs1859962, rs4430796 and rs5945572. An overall risk for prostate cancer and/or colon cancer is in one embodiment calculated based on the genotype status of the individual.

In certain embodiments, the susceptibility is increased susceptibility. Increased susceptibility is in certain embodiments accompanied by an odds ratio (OR) or relative risk (RR) of at least 1.10. In other embodiments, the odds ratio or relative risk is at least 1.15. In other embodiments, the relative risk or odds ratio is at least 1.20. In one embodiment, the at least one marker or haplotype comprises marker rs10896450 allele G, marker rs7947353 allele A and marker rs10943605 allele G.

In certain other embodiments, the susceptibility is decreased susceptibility. The decreased susceptibility is in some embodiments accompanied by a relative risk or odds ratio of less than 0.9.

Certain embodiments of the invention relate to aggressive forms of prostate cancer. In some embodiments, the prostate cancer is an aggressive prostate cancer as defined by a combined Gleason score of 7(4+3)−10. In other embodiments, the prostate cancer is a less aggressive prostate cancer as defined by a combined Gleason score of 2−7(3+4).

In certain embodiments of the invention, the individual is of a specific ancestry. One embodiment relates to the ancestry being Caucasian ancestry. In other embodiments, the ancestry is African ancestry or African American ancestry. In another embodiment, the ancestry is European ancestry. The ancestry is in some embodiment self-reported. In other embodiments, the ancestry is determined by detecting at least one allele of at least one polymorphic marker in a sample from the individual, wherein the presence or absence of the allele is indicative of the ancestry of the individual.

In certain embodiments of the invention, linkage disequilibrium is determined using the linkage disequilibrium measures r² and |D′|, which give a quantitative measure of the extent of linkage disequilibrium (LD) between two genetic element (e.g., polymorphic markers). Certain numerical values of these measures for particular markers are indicative of the markers being in linkage disequilibrium, as described further herein. The higher the numerical value for the LD measures r² and |D′|, the stronger the LD between the genetic elements is, as further described herein. In one embodiment of the invention, linkage disequilibrium between marker (i.e., LD values indicative of the markers being in linkage disequilibrium) is defined as r²>0.1. In another embodiment, linkage disequilibrium is defined as r²>0.2. Other embodiments can include other definitions of linkage disequilibrium, such as r²>0.25, r²>0.3, r²>0.35, r²>0.4, r²>0.45, r²>0.5, r²>0.55, r²>0.6, r²>0.65, r²>0.7, r²>0.75, r²>0.8, r²>0.85, r²>0.9, r²>0.95, r²>0.96, r²>0.97, r²>0.98, or r²>0.99. Linkage disequilibrium can in certain embodiments also be defined as |D′|>0.2, or as |D′|>0.3, |D′|>0.4, |D′|>0.5, |D′|>0.6, |D′|>0.7, |D′|>0.8, |D′|>0.9, |D′|>0.95, |D′|>0.98 or |D′|>0.99. In certain embodiments, linkage disequilibrium is defined as fulfilling two criteria of r² and |D′|, such as r²>0.2 and/or |D′|>0.8. Other combinations of values for r² and |D′| are also possible and within scope of the present invention, including but not limited to the values for these parameters set forth in the above.

It should be understood that all combinations of features described herein are contemplated, even if the combination of feature is not specifically found in the same sentence or paragraph herein. This includes, but is not limited to, the use of all markers disclosed herein, alone or in combination, for analysis individually or in haplotypes, in all aspects of the invention as described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention.

The FIGURE provides a diagram illustrating a computer-implemented system utilizing risk variants as described herein.

DETAILED DESCRIPTION OF THE INVENTION

The present invention discloses polymorphic variants and haplotypes that have been found to be associated with prostate and colorectal cancer. Such markers and haplotypes are useful for diagnostic purposes, as described in further detail herein.

DEFINITIONS

Unless otherwise indicated, nucleic acid sequences are written left to right in a 5′ to 3′ orientation. Numeric ranges recited within the specification are inclusive of the numbers defining the range and include each integer or any non-integer fraction within the defined range. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by the ordinary person skilled in the art to which the invention pertains.

The following terms shall, in the present context, have the meaning as indicated:

A “polymorphic marker”, sometimes referred to as a “marker”, as described herein, refers to a genomic polymorphic site. Each polymorphic marker has at least two sequence variations characteristic of particular alleles at the polymorphic site. Thus, genetic association to a polymorphic marker implies that there is association to at least one specific allele of that particular polymorphic marker. The marker can comprise any allele of any variant type found in the genome, including SNPs, mini- or microsatellites, translocations and copy number variations (insertions, deletions, duplications). Polymorphic markers can be of any measurable frequency in the population. For mapping of disease genes, polymorphic markers with population frequency higher than 5-10% are in general most useful. However, polymorphic markers may also have lower population frequencies, such as 1-5% frequency, or even lower frequency, in particular copy number variations (CNVs). The term shall, in the present context, be taken to include polymorphic markers with any population frequency.

An “allele” refers to the nucleotide sequence of a given locus (position) on a chromosome. A polymorphic marker allele thus refers to the composition (i.e., sequence) of the marker on a chromosome. Genomic DNA from an individual contains two alleles for any given polymorphic marker, representative of each copy of the marker on each chromosome. Sequence codes for nucleotides used herein are: A=1, C=2, G=3, T=4. For microsatellite alleles, the CEPH sample (Centre d'Etudes du Polymorphisme Humain, genomics repository, CEPH sample 1347-02) is used as a reference, the shorter allele of each microsatellite in this sample is set as 0 and all other alleles in other samples are numbered in relation to this reference. Thus, e.g., allele 1 is 1 bp longer than the shorter allele in the CEPH sample, allele 2 is 2 bp longer than the shorter allele in the CEPH sample, allele 3 is 3 bp longer than the lower allele in the CEPH sample, etc., and allele −1 is 1 bp shorter than the shorter allele in the CEPH sample, allele −2 is 2 bp shorter than the shorter allele in the CEPH sample, etc.

Sequence conucleotide ambiguity as described herein is as proposed by IUPAC-IUB. These codes are compatible with the codes used by the EMBL, GenBank, and PIR databases.

IUB code Meaning A Adenosine C Cytidine G Guanine T Thymidine R G or A Y T or C K G or T M A or C S G or C W A or T B C, G or T D A, G or T H A, C or T V A, C or G N A, C, G or T (Any base)

A nucleotide position at which more than one sequence is possible in a population (either a natural population or a synthetic population, e.g., a library of synthetic molecules) is referred to herein as a “polymorphic site”.

A “Single Nucleotide Polymorphism” or “SNP” is a DNA sequence variation occurring when a single nucleotide at a specific location in the genome differs between members of a species or between paired chromosomes in an individual. Most SNP polymorphisms have two alleles. Each individual is in this instance either homozygous for one allele of the polymorphism (i.e. both chromosomal copies of the individual have the same nucleotide at the SNP location), or the individual is heterozygous (i.e. the two sister chromosomes of the individual contain different nucleotides). The SNP nomenclature as reported herein refers to the official Reference SNP (rs) ID identification tag as assigned to each unique SNP by the National Center for Biotechnological Information (NCBI).

A “variant”, as described herein, refers to a segment of DNA that differs from the reference DNA. A “marker” or a “polymorphic marker”, as defined herein, is a variant. Alleles that differ from the reference are referred to as “variant” alleles.

A “microsatellite” is a polymorphic marker that has multiple small repeats of bases that are 2-8 nucleotides in length (such as CA repeats) at a particular site, in which the number of repeat lengths varies in the general population.

An “indel” is a common form of polymorphism comprising a small insertion or deletion that is typically only a few nucleotides long.

A “haplotype,” as described herein, refers to a segment of genomic DNA within one strand of DNA that is characterized by a specific combination of alleles arranged along the segment. For diploid organisms such as humans, a haplotype comprises one member of the pair of alleles for each polymorphic marker or locus along the segment. In a certain embodiment, the haplotype can comprise two or more alleles, three or more alleles, four or more alleles, or five or more alleles. Haplotypes are described herein in the context of the marker name and the allele of the marker in that haplotype, e.g., “3 rs10896450” refers to the 3 allele of marker rs10896450 being in the haplotype, and is equivalent to “rs10896450 allele 3”. Furthermore, allelic codes in haplotypes are as for individual markers, i.e. 1=A, 2=C, 3=G and 4=T.

The term “susceptibility”, as described herein, encompasses both increased susceptibility and decreased susceptibility. Thus, particular polymorphic markers and/or haplotypes of the invention may be characteristic of increased susceptibility (i.e., increased risk) of prostate cancer, as characterized by a relative risk (RR) or odds ratio (OR) of greater than one for the particular allele or haplotype. Alternatively, the markers and/or haplotypes of the invention are characteristic of decreased susceptibility (i.e., decreased risk) of prostate cancer, as characterized by a relative risk of less than one.

The term “and/or” shall in the present context be understood to indicate that either or both of the items connected by it are involved. In other words, the term herein shall be taken to mean “one or the other or both”.

The term “look-up table”, as described herein, is a table that correlates one form of data to another form, or one or more forms of data to a predicted outcome to which the data is relevant, such as phenotype or trait. For example, a look-up table can comprise a correlation between allelic data for at least one polymorphic marker and a particular trait or phenotype, such as a particular disease diagnosis, that an individual who comprises the particular allelic data is likely to display, or is more likely to display than individuals who do not comprise the particular allelic data. Look-up tables can be multidimensional, i.e. they can contain information about multiple alleles for single markers simultaneously, or the can contain information about multiple markers, and they may also comprise other factors, such as particulars about diseases diagnoses, racial information, biomarkers, biochemical measurements, therapeutic methods or drugs, etc.

A “computer-readable medium”, is an information storage medium that can be accessed by a computer using a commercially available or custom-made interface. Exemplary compute-readable media include memory (e.g., RAM, ROM, flash memory, etc.), optical storage media (e.g., CD-ROM), magnetic storage media (e.g., computer hard drives, floppy disks, etc.), punch cards, or other commercially available media. Information may be transferred between a system of interest and a medium, between computers, or between computers and the computer-readable medium for storage or access of stored information. Such transmission can be electrical, or by other available methods, such as IR links, wireless connections, etc.

A “nucleic acid sample”, as described herein, refer to a sample obtained from an individual that contains nucleic acid (DNA or RNA). In certain embodiments, i.e. the detection of specific polymorphic markers and/or haplotypes, the nucleic acid sample comprises genomic DNA. Such a nucleic acid sample can be obtained from any source that contains genomic DNA, including as a blood sample, sample of amniotic fluid, sample of cerebrospinal fluid, or tissue sample from skin, muscle, buccal or conjunctival mucosa, placenta, gastrointestinal tract or other organs.

The term “prostate cancer therapeutic agent” and “colorectal cancer therapeutic agent”, as described herein, refers to an agent that can be used to ameliorate or prevent symptoms associated with prostate cancer and colorectal cancer, respectively.

The term “prostate cancer-associated nucleic acid” and “colorectal cancer-associated nucleic acid”, as described herein, refers to a nucleic acid that has been found to be associated to prostate and/or colorectal cancer. This includes, but is not limited to, the markers and haplotypes described herein and markers and haplotypes in strong linkage disequilibrium (LD) therewith. In one embodiment, a prostate and/or colon cancer-associated nucleic acid refers to an LD-block found to be associated with prostate and/or colorectal cancer through at least one polymorphic marker located within the LD block C06 or associated with the LD block C11.

“Aggressive prostate cancer”, as described herein, refers to prostate cancer with combined Gleason grades of 7 or higher OR stage T3 or higher OR node positive OR metastasis positive disease OR death because of prostate cancer. Note that it is sufficient to have one of these criteria to be determined aggressive prostate cancer. These clinical parameters are well known surrogates for increased aggressiveness of the disease.

The term “LD block 06”, as described herein, refers to the Linkage Disequilibrium (LD) block on Chromosome 6 between positions 79,300,773 and 79,917,888 of NCBI (National Center for Biotechnology Information) Build 36, spanning the region flanked by the SNP markers rs611737 and rs9294130.

The term “LD block C11”, as described herein, refers to the Linkage Disequilibrium (LD) block on Chromosome 11 between positions 68,709,630 and 68,782,375 of NCBI (National Center for Biotechnology Information) Build 36, spanning the region flanked by the SNP markers rs7128814 and rs3884627. The LD block C11 has the sequence as set forth in SEQ ID NO:201 herein, based on NCBI Build 36 of the human genome sequence assembly.

A genome-wide search for variants associated with prostate and/or colorectal cancer has identified two genomic regions associated with these cancers. Markers rs10896450 and rs7947353 on Chr 11q13.3, within a region herein called LD Block C11, were identified as contributing to risk of prostate cancer (see Table 1). The two markers are fully correlated (D′=1 and r²=1; see footnote of Table 1) and do therefore essentially represent the same association signal. The G allele of SNP marker rs10896450 confers increased risk of prostate cancer, with an odds ratio (OR) of 1.17 in the Icelandic samples (P=6.6×10⁻⁵). The initial discovery in an Icelandic prostate cancer cohort was validated by analysis of marker rs7947353, which is perfectly correlated (i.e., a perfect surrogate marker) to rs10896450, in prostate cancer cohorts from the Netherlands, Spain and US (Chicago, Ill.). The results for these additional cohorts are comparable to the results for the Icelandic discovery cohort, showing that the initial observation represents a true association signal. Overall, the association is significant with a p-value of 1.43×10⁻⁶.

A follow-up analysis revealed that marker rs11228565, located within LD Block C11, shows that this marker associated very significantly with prostate cancer, with an OR of 1.23 for all cohorts and an overall P-value of 6.7×10⁻¹² (Table 7).

A second region on Chromosome 6 (LD Block C06) was identified as a prostate cancer susceptibility region, as shown in Table 2a. The association of the G allele of the rs10943605 SNP marker observed in the Icelandic cohort was replicated in Dutch and Spanish cohort, both which gave increased risk conferred by the G allele, although only the replication in the Dutch cohort is statistically significant. Surprisingly, the G allele of the rs10943605 SNP marker was also found to be associated with increased risk of developing colorectal cancer, with an OR of 1.14 in the Icelandic colorectal cancer samples (P=4.8×10⁻³) (Table 2b).

Accordingly, the present invention provides methods for determining a susceptibility to prostate cancer and colorectal cancer, by assessing for the presence or absence of particular alleles of polymorphic markers within the LD Block C06 and/or LD Block C11 genomic segments that are indicative of risk of prostate cancer and colorectal cancer. Determination of the presence of such marker alleles is indicative of risk of prostate cancer and/or colorectal cancer in the individual.

Assessment for Markers and Haplotypes

The genomic sequence within populations is not identical when individuals are compared. Rather, the genome exhibits sequence variability between individuals at many locations in the genome. Such variations in sequence are commonly referred to as polymorphisms, and there are many such sites within each genome For example, the human genome exhibits sequence variations which occur on average every 500 base pairs. The most common sequence variant consists of base variations at a single base position in the genome, and such sequence variants, or polymorphisms, are commonly called Single Nucleotide Polymorphisms (“SNPs”). These SNPs are believed to have occurred in a single mutational event, and therefore there are usually two possible alleles possible at each SNP site; the original allele and the mutated allele. Due to natural genetic drift and possibly also selective pressure, the original mutation has resulted in a polymorphism characterized by a particular frequency of its alleles in any given population. Many other types of sequence variants are found in the human genome, including mini- and microsatellites, and insertions, deletions and inversions (also called copy number variations (CNVs)). A polymorphic microsatellite has multiple small repeats of bases (such as CA repeats, TG on the complimentary strand) at a particular site in which the number of repeat lengths varies in the general population. In general terms, each version of the sequence with respect to the polymorphic site represents a specific allele of the polymorphic site. These sequence variants can all be referred to as polymorphisms, occurring at specific polymorphic sites characteristic of the sequence variant in question. In general terms, polymorphisms can comprise any number of specific alleles. Thus in one embodiment of the invention, the polymorphism is characterized by the presence of two or more alleles in any given population. In another embodiment, the polymorphism is characterized by the presence of three or more alleles. In other embodiments, the polymorphism is characterized by four or more alleles, five or more alleles, six or more alleles, seven or more alleles, nine or more alleles, or ten or more alleles. All such polymorphisms can be utilized in the methods and kits of the present invention, and are thus within the scope of the invention.

Due to their abundance, SNPs account for a majority of sequence variation in the human genome. Over 6 million SNPs have been validated to date (ncbi.nlm.nih.gov/projects/SNP/snp_summary.cgi). However, CNVs are receiving increased attention. These large-scale polymorphisms (typically 1 kb or larger) account for polymorphic variation affecting a substantial proportion of the assembled human genome; known CNVs cover over 15% of the human genome sequence (Estivill, X., Armengol; L., PloS Genetics 3:1787-99 (2007). A http://projects.tcag.ca/variation/). Most of these polymorphisms are however very rare, and on average affect only a fraction of the genomic sequence of each individual. CNVs are known to affect gene expression, phenotypic variation and adaptation by disrupting gene dosage, and are also known to cause disease (microdeletion and microduplication disorders) and confer risk of common complex diseases, including HIV-1 infection and glomerulonephritis (Redon, R., et al. Nature 23:444-454 (2006)). It is thus possible that either previously described or unknown CNVs represent causative variants in linkage disequilibrium with the markers described herein to be associated with prostate and colorectal cancer. Methods for detecting CNVs include comparative genomic hybridization (CGH) and genotyping, including use of genotyping arrays, as described by Carter (Nature Genetics 39:S16-S21 (2007)). The Database of Genomic Variants (http://projects.tcag.ca/variation/) contains updated information about the location, type and size of described CNVs. The database currently contains data for over 15,000 CNVs.

In some instances, reference is made to different alleles at a polymorphic site without choosing a reference allele. Alternatively, a reference sequence can be referred to for a particular polymorphic site. The reference allele is sometimes referred to as the “wild-type” allele and it usually is chosen as either the first sequenced allele or as the allele from a “non-affected” individual (e.g., an individual that does not display a trait or disease phenotype).

Alleles for SNP markers as referred to herein refer to the bases A, C, G or T as they occur at the polymorphic site in the SNP assay employed. The allele codes for SNPs used herein are as follows: 1=A, 2=C, 3=G, 4=T. The person skilled in the art will however realise that by assaying or reading the opposite DNA strand, the complementary allele can in each case be measured. Thus, for a polymorphic site (polymorphic marker) characterized by an A/G polymorphism, the assay employed may be designed to specifically detect the presence of one or both of the two bases possible, e.g. A and G. Alternatively, by designing an assay that is designed to detect the complimentary strand on the DNA template, the presence of the complementary bases T and C can be measured. Quantitatively (for example, in terms of risk estimates), identical results would be obtained from measurement of either DNA strand (+ strand or − strand).

Typically, a reference sequence is referred to for a particular sequence. Alleles that differ from the reference are sometimes referred to as “variant” alleles. A variant sequence, as used herein, refers to a sequence that differs from the reference sequence but is otherwise substantially similar. Alleles at the polymorphic genetic markers described herein are variants. Additional variants can include changes that affect a polypeptide. Sequence differences, when compared to a reference nucleotide sequence, can include the insertion or deletion of a single nucleotide, or of more than one nucleotide, resulting in a frame shift; the change of at least one nucleotide, resulting in a change in the encoded amino acid; the change of at least one nucleotide, resulting in the generation of a premature stop codon; the deletion of several nucleotides, resulting in a deletion of one or more amino acids encoded by the nucleotides; the insertion of one or several nucleotides, such as by unequal recombination or gene conversion, resulting in an interruption of the coding sequence of a reading frame; duplication of all or a part of a sequence; transposition; or a rearrangement of a nucleotide sequence. Such sequence changes can alter the polypeptide encoded by the nucleic acid. For example, if the change in the nucleic acid sequence causes a frame shift, the frame shift can result in a change in the encoded amino acids, and/or can result in the generation of a premature stop codon, causing generation of a truncated polypeptide. Alternatively, a polymorphism associated with a disease or trait can be a synonymous change in one or more nucleotides (i.e., a change that does not result in a change in the amino acid sequence). Such a polymorphism can, for example, alter splice sites, affect the stability or transport of mRNA, or otherwise affect the transcription or translation of an encoded polypeptide. It can also alter DNA to increase the possibility that structural changes, such as amplifications or deletions, occur at the somatic level. The polypeptide encoded by the reference nucleotide sequence is the “reference” polypeptide with a particular reference amino acid sequence, and polypeptides encoded by variant alleles are referred to as “variant” polypeptides with variant amino acid sequences.

A haplotype refers to a segment of DNA that is characterized by a specific combination of alleles arranged along the segment. For diploid organisms such as humans, a haplotype comprises one member of the pair of alleles for each polymorphic marker or locus. In a certain embodiment, the haplotype can comprise two or more alleles, three or more alleles, four or more alleles, or five or more alleles, each allele corresponding to a specific polymorphic marker along the segment. Haplotypes can comprise a combination of various polymorphic markers, e.g., SNPs and microsatellites, having particular alleles at the polymorphic sites. The haplotypes thus comprise a combination of alleles at various genetic markers.

Detecting specific polymorphic markers and/or haplotypes can be accomplished by methods known in the art for detecting sequences at polymorphic sites. For example, standard techniques for genotyping for the presence of SNPs and/or microsatellite markers can be used, such as fluorescence-based techniques (Chen, X. et al., Genome Res. 9(5): 492-98 (1999); Kutyavin et al., Nucleic Acid Res. 34:e128 (2006)), utilizing PCR, LCR, Nested PCR and other techniques for nucleic acid amplification. Specific methodologies available for SNP genotyping include, but are not limited to, TaqMan genotyping assays and SNPlex platforms (Applied Biosystems), mass spectrometry (e.g., MassARRAY system from Sequenom), minisequencing methods, real-time PCR, Bio-Plex system (BioRad), CEQ and SNPstream systems (Beckman), Molecular Inversion Probe array technology (e.g., Affymetrix GeneChip), and BeadArray Technologies (e.g., Illumina GoldenGate and Infinium assays). By these or other methods available to the person skilled in the art, one or more alleles at polymorphic markers, including microsatellites, SNPs or other types of polymorphic markers, can be identified.

In the present context, and individual who is at an increased susceptibility (i.e., increased risk) for a disease, is an individual in whom at least one specific allele at one or more polymorphic marker or haplotype conferring increased susceptibility (increased risk) for the disease is identified (i.e., at-risk marker alleles or haplotypes). The at-risk marker or haplotype is one that confers an increased risk (increased susceptibility) of the disease. In one embodiment, significance associated with a marker or haplotype is measured by a relative risk (RR). In another embodiment, significance associated with a marker or haplotye is measured by an odds ratio (OR). In a further embodiment, the significance is measured by a percentage. In one embodiment, a significant increased risk is measured as a risk (relative risk and/or odds ratio) of at least 1.2, including but not limited to: at least 1.2, at least 1.3, at least 1.4, at least 1.5, at least 1.6, at least 1.7, 1.8, at least 1.9, at least 2.0, at least 2.5, at least 3.0, at least 4.0, and at least 5.0. In a particular embodiment, a risk (relative risk and/or odds ratio) of at least 1.2 is significant. In another particular embodiment, a risk of at least 1.3 is significant. In yet another embodiment, a risk of at least 1.4 is significant. In a further embodiment, a relative risk of at least 1.5 is significant. In another further embodiment, a significant increase in risk is at least 1.7 is significant. However, other cutoffs are also contemplated, e.g., at least 1.15, 1.25, 1.35, and so on, and such cutoffs are also within scope of the present invention. In other embodiments, a significant increase in risk is at least about 20%, including but not limited to about 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 100%, 150%, 200%, 300%, and 500%. In one particular embodiment, a significant increase in risk is at least 20%. In other embodiments, a significant increase in risk is at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% and at least 100%. Other cutoffs or ranges as deemed suitable by the person skilled in the art to characterize the invention are however also contemplated, and those are also within scope of the present invention. In certain embodiments, a significant increase in risk is characterized by a p-value, such as a p-value of less than 0.05, less than 0.01, less than 0.001, less than 0.0001, less than 0.00001, less than 0.000001, less than 0.0000001, less than 0.00000001, or less than 0.000000001.

An at-risk polymorphic marker or haplotype of the present invention is one where at least one allele of at least one marker or haplotype is more frequently present in an individual at risk for the disease or trait (affected), compared to the frequency of its presence in a comparison group (control), and wherein the presence of the marker or haplotype is indicative of susceptibility to the disease or trait. The control group may in one embodiment be a population sample, i.e. a random sample from the general population. In another embodiment, the control group is represented by a group of individuals who are disease-free. Such disease-free control may in one embodiment be characterized by the absence of one or more specific disease-associated symptoms. In another embodiment, the disease-free control group is characterized by the absence of one or more disease-specific risk factors. Such risk factors are in one embodiment at least one environmental risk factor. Representative environmental factors are natural products, minerals or other chemicals which are known to affect, or contemplated to affect, the risk of developing the specific disease or trait. Other environmental risk factors are risk factors related to lifestyle, including but not limited to food and drink habits, geographical location of main habitat, and occupational risk factors. In another embodiment, the risk factors are at least one genetic risk factor.

As an example of a simple test for correlation would be a Fisher-exact test on a two by two table. Given a cohort of chromosomes, the two by two table is constructed out of the number of chromosomes that include both of the markers or haplotypes, one of the markers or haplotypes but not the other and neither of the markers or haplotypes.

In other embodiments of the invention, an individual who is at a decreased susceptibility (i.e., at a decreased risk) for a disease or trait is an individual in whom at least one specific allele at one or more polymorphic marker or haplotype conferring decreased susceptibility for the disease or trait is identified. The marker alleles and/or haplotypes conferring decreased risk are also said to be protective. In one aspect, the protective marker or haplotype is one that confers a significant decreased risk (or susceptibility) of the disease or trait. In one embodiment, significant decreased risk is measured as a relative risk of less than 0.9, including but not limited to less than 0.9, less than 0.8, less than 0.7, less than 0.6, less than 0.5, less than 0.4, less than 0.3, less than 0.2 and less than 0.1. In one particular embodiment, significant decreased risk is less than 0.7. In another embodiment, significant decreased risk is less than 0.5. In yet another embodiment, significant decreased risk is less than 0.3. In another embodiment, the decrease in risk (or susceptibility) is at least 20%, including but not limited to at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95% and at least 98%. In one particular embodiment, a significant decrease in risk is at least about 30%. In another embodiment, a significant decrease in risk is at least about 50%. In another embodiment, the decrease in risk is at least about 70%. Other cutoffs or ranges as deemed suitable by the person skilled in the art to characterize the invention are however also contemplated, and those are also within scope of the present invention.

The person skilled in the art will appreciate that for markers with two alleles present in the population being studied (such as SNPs), and wherein one allele is found in increased frequency in a group of individuals with a trait or disease in the population, compared with controls, the other allele of the marker will be found in decreased frequency in the group of individuals with the trait or disease, compared with controls. In such a case, one allele of the marker (the one found in increased frequency in individuals with the trait or disease) will be the at-risk allele, while the other allele will be a protective allele.

A genetic variant associated with a disease or a trait can be used alone to predict the risk of the disease for a given genotype. For a biallelic marker, such as a SNP, there are 3 possible genotypes: homozygote for the at risk variant, heterozygote, and non carrier of the at risk variant. Risk associated with variants at multiple loci can be used to estimate overall risk. For multiple SNP variants, there are k possible genotypes k=3^(n)×2^(p); where n is the number autosomal loci and p the number of gonosomal (sex chromosomal) loci. Overall risk assessment calculations for a plurality of risk variants usually assume that the relative risks of different genetic variants multiply, i.e. the overall risk (e.g., RR or OR) associated with a particular genotype combination is the product of the risk values for the genotype at each locus. If the risk presented is the relative risk for a person, or a specific genotype for a person, compared to a reference population with matched gender and ethnicity, then the combined risk—is the product of the locus specific risk values—and which also corresponds to an overall risk estimate compared with the population. If the risk for a person is based on a comparison to non-carriers of the at risk allele, then the combined risk corresponds to an estimate that compares the person with a given combination of genotypes at all loci to a group of individuals who do not carry risk variants at any of those loci. The group of non-carriers of any at risk variant has the lowest estimated risk and has a combined risk, compared with itself (i.e., non-carriers) of 1.0, but has an overall risk, compare with the population, of less than 1.0. It should be noted that the group of non-carriers can potentially be very small, especially for large number of loci, and in that case, its relevance is correspondingly small.

The multiplicative model is a parsimonious model that usually fits the data of complex traits reasonably well. Deviations from multiplicity have been rarely described in the context of common variants for common diseases, and if reported are usually only suggestive since very large sample sizes are usually required to be able to demonstrate statistical interactions between loci.

By way of an example, let us consider variants in eight regions (loci) that have been described to associate with prostate cancer (Gudmundsson, J., et al., Nat Genet 39:631-7 (2007), Gudmundsson, J., et al., Nat Genet 39:977-83 (2007); Yeager, M., et al, Nat Genet 39:645-49 (2007), Amundadottir, L., et al., Nat Genet 38:652-8 (2006); Haiman, C. A., et al., Nat Genet 39:638-44 (2007)). Seven of these loci are on autosomes, and the remaining locus is on chromosome X. The total number of theoretical genotypic combinations is then 3⁷×2¹=4374. Some of those genotypic classes are very rare, but are still possible, and should be considered for overall risk assessment. It is likely that the multiplicative model applied in the case of multiple genetic variant will also be valid in conjugation with non-genetic risk variants assuming that the genetic variant does not clearly correlate with the “environmental” factor. In other words, genetic and non-genetic at-risk variants can be assessed under the multiplicative model to estimate combined risk, assuming that the non-genetic and genetic risk factors do not interact.

Accordingly, in certain embodiments, therefore, the markers shown herein to be predictive of risk of prostate cancer in humans can be used in combination with any one, or a combination of, rs2710646 allele A, rs16901979 allele A, rs1447295 allele A, rs6983267 allele G, rs10896450 allele G, rs1859962 allele G, rs4430796 allele A and rs5945572 allele A. In a preferred embodiment, the at-risk markers for prostate cancer as described herein are assessed together with rs2710646 allele A, rs 16901979 allele A, rs1447295 allele A, rs6983267 allele G, rs10896450 allele G, rs1859962 allele G, rs4430796 allele A and rs5945572 allele A to determine overall risk of prostate cancer in an individual.

The skilled person will realize that the markers presented herein may also be assessed in combination with any other genetic risk factors for prostate cancer and/or colorectal cancer, so as to determine overall risk of the cancer in an individual.

Linkage Disequilibrium

The natural phenomenon of recombination, which occurs on average once for each chromosomal pair during each meiotic event, represents one way in which nature provides variations in sequence (and biological function by consequence). It has been discovered that recombination does not occur randombly in the genome; rather, there are large variations in the frequency of recombination rates, resulting in small regions of high recombination frequency (also called recombination hotspots) and larger regions of low recombination frequency, which are commonly referred to as Linkage Disequilibrium (LD) blocks (Myers, S. et al., Biochem Soc Trans 34:526-530 (2006); Jeffreys, A. J., et al., Nature Genet. 29:217-222 (2001); May, C. A., et al., Nature Genet. 31:272-275 (2002)).

Linkage Disequilibrium (LD) refers to a non-random assortment of two genetic elements. For example, if a particular genetic element (e.g., an allele of a polymorphic marker, or a haplotype) occurs in a population at a frequency of 0.50 (50%) and another element occurs at a frequency of 0.50 (50%), then the predicted occurrance of a person's having both elements is 0.25 (25%), assuming a random distribution of the elements. However, if it is discovered that the two elements occur together at a frequency higher than 0.25, then the elements are said to be in linkage disequilibrium, since they tend to be inherited together at a higher rate than what their independent frequencies of occurrence (e.g., allele or haplotype frequencies) would predict. Roughly speaking, LD is generally correlated with the frequency of recombination events between the two elements. Allele or haplotype frequencies can be determined in a population by genotyping individuals in a population and determining the frequency of the occurence of each allele or haplotype in the population. For populations of diploids, e.g., human populations, individuals will typically have two alleles for each genetic element (e.g., a marker, haplotype or gene).

Many different measures have been proposed for assessing the strength of linkage disequilibrium (LD; reviewed in Devlin, B. & Risch, N., Genomics 29:311-22 (1995))). Most capture the strength of association between pairs of biallelic sites. Two important pairwise measures of LD are r² (sometimes denoted Δ²) and |D′| (Lewontin, R., Genetics 49:49-67 (1964); Hill, W. G. & Robertson, A. Theor. Appl. Genet. 22:226-231 (1968)). Both measures range from 0 (no disequilibrium) to 1 (‘complete’ disequilibrium), but their interpretation is slightly different. |D′| is defined in such a way that it is equal to 1 if just two or three of the possible haplotypes are present, and it is <1 if all four possible haplotypes are present. Therefore, a value of |D′| that is <1 indicates that historical recombination may have occurred between two sites (recurrent mutation can also cause |D′| to be <1, but for single nucleotide polymorphisms (SNPs) this is usually regarded as being less likely than recombination). The measure r² represents the statistical correlation between two sites, and takes the value of 1 if only two haplotypes are present.

The r² measure is arguably the most relevant measure for association mapping, because there is a simple inverse relationship between r² and the sample size required to detect association between susceptibility loci and SNPs. These measures are defined for pairs of sites, but for some applications a determination of how strong LD is across an entire region that contains many polymorphic sites might be desirable (e.g., testing whether the strength of LD differs significantly among loci or across populations, or whether there is more or less LD in a region than predicted under a particular model). Measuring LD across a region is not straightforward, but one approach is to use the measure r, which was developed in population genetics. Roughly speaking, r measures how much recombination would be required under a particular population model to generate the LD that is seen in the data. This type of method can potentially also provide a statistically rigorous approach to the problem of determining whether LD data provide evidence for the presence of recombination hotspots. For the methods described herein, a significant r² value can be at least 0.1 such as at least 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, 0.99 or 1.0. In one preferred embodiment, the significant r² value can be at least 0.2. Alternatively, linkage disequilibrium as described herein, refers to linkage disequilibrium characterized by values of |D′| of at least 0.2, such as 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.85, 0.9, 0.95, 0.96, 0.97, 0.98, 0.99. Thus, linkage disequilibrium represents a correlation between alleles of distinct markers. It is measured by correlation coefficient or |D′| (r² up to 1.0 and |D′| up to 1.0). In certain embodiments, linkage disequilibrium is defined in terms of values for both the r² and |D′| measures. In one such embodiment, a significant linkage disequilibrium is defined as r²>0.2 and/or |D′|>0.8. In another embodiment, a significant linkage disequilibrium is defined as r²>0.2 and/or |D′|>0.9. Other combinations and permutations of values of r² and |D′| for determining linkage disequilibrium are also possible, and within the scope of the invention. Linkage disequilibrium can be determined in a single human population, as defined herein, or it can be determined in a collection of samples comprising individuals from more than one human population. In one embodiment of the invention, LD is determined in a sample from one or more of the HapMap populations (caucasian, african, japanese, chinese), as defined (http://www.hapmap.org). In one such embodiment, LD is determined in the CEU population of the HapMap samples. In another embodiment, LD is determined in the YRI population. In yet another embodiment, LD is determined in samples from the Icelandic population.

If all polymorphisms in the genome were identical at the population level, then every single one of them would need to be investigated in association studies. However, due to linkage disequilibrium between polymorphisms, tightly linked polymorphisms are strongly correlated, which reduces the number of polymorphisms that need to be investigated in an association study to observe a significant association. Another consequence of LD is that many polymorphisms may give an association signal due to the fact that these polymorphisms are strongly correlated.

Genomic LD maps have been generated across the genome, and such LD maps have been proposed to serve as framework for mapping disease-genes (Risch, N. & Merkiangas, K, Science 273:1516-1517 (1996); Maniatis, N., et al., Proc Natl Acad Sci USA 99:2228-2233 (2002); Reich, D E et al, Nature 411:199-204 (2001)).

It is now established that many portions of the human genome can be broken into series of discrete haplotype blocks containing a few common haplotypes; for these blocks, linkage disequilibrium data provides little evidence indicating recombination (see, e.g., Wall., J. D. and Pritchard, J. K., Nature Reviews Genetics 4:587-597 (2003); Daly, M. et al., Nature Genet. 29:229-232 (2001); Gabriel, S. B. et al., Science 296:2225-2229 (2002); Patil, N. et al., Science 294:1719-1723 (2001); Dawson, E. et al., Nature 418:544-548 (2002); Phillips, M. S. et al., Nature Genet. 33:382-387 (2003)).

There are two main methods for defining these haplotype blocks: blocks can be defined as regions of DNA that have limited haplotype diversity (see, e.g., Daly, M. et al., Nature Genet. 29:229-232 (2001); Patil, N. et al., Science 294:1719-1723 (2001); Dawson, E. et al., Nature 418:544-548 (2002); Zhang, K. et al., Proc. Natl. Acad. Sci. USA 99:7335-7339 (2002)), or as regions between transition zones having extensive historical recombination, identified using linkage disequilibrium (see, e.g., Gabriel, S. B. et al., Science 296:2225-2229 (2002); Phillips, M. S. et al., Nature Genet. 33:382-387 (2003); Wang, N. et al., Am. J. Hum. Genet. 71:1227-1234 (2002); Stumpf, M. P., and Goldstein, D. B., Curr. Biol. 13:1-8 (2003)). More recently, a fine-scale map of recombination rates and corresponding hotspots across the human genome has been generated (Myers, S., et al., Science 310:321-32324 (2005); Myers, S. et al., Biochem Soc Trans 34:526530 (2006)). The map reveals the enormous variation in recombination across the genome, with recombination rates as high as 10-60 cM/Mb in hotspots, while closer to 0 in intervening regions, which thus represent regions of limited haplotype diversity and high LD. The map can therefore be used to define haplotype blocks/LD blocks as regions flanked by recombination hotspots. As used herein, the terms “haplotype block” or “LD block” includes blocks defined by any of the above described characteristics, or other alternative methods used by the person skilled in the art to define such regions.

Haplotype blocks can be used to map associations between phenotype and haplotype status, using single markers or haplotypes comprising a plurality of markers. The main haplotypes can be identified in each haplotype block, and then a set of “tagging” SNPs or markers (the smallest set of SNPs or markers needed to distinguish among the haplotypes) can then be identified. These tagging SNPs or markers can then be used in assessment of samples from groups of individuals, in order to identify association between phenotype and haplotype. If desired, neighboring haplotype blocks can be assessed concurrently, as there may also exist linkage disequilibrium among the haplotype blocks.

It has thus become apparent that for any given observed association to a polymorphic marker in the genome, it is likely that additional markers in the genome also show association. This is a natural consequence of the uneven distribution of LD across the genome, as observed by the large variation in recombination rates. The markers used to detect association thus in a sense represent “tags” for a genomic region (i.e., a haplotype block or LD block) that is associating with a given disease or trait, and as such are useful for use in the methods and kits of the present invention. One or more causative (functional) variants or mutations may reside within the region found to be associating to the disease or trait. The functional variant may be another SNP, a tandem repeat polymorphism (such as a minisatellite or a microsatellite), a transposable element, or a copy number variation, such as an inversion, deletion or insertion. Such variants in LD with the variants described herein may confer a higher relative risk (RR) or odds ratio (OR) than observed for the tagging markers used to detect the association. The present invention thus refers to the markers used for detecting association to the disease, as described herein, as well as markers in linkage disequilibrium with the markers. Thus, in certain embodiments of the invention, markers that are in LD with the markers and/or haplotypes of the invention, as described herein, may be used as surrogate markers. The surrogate markers have in one embodiment relative risk (RR) and/or odds ratio (OR) values smaller than for the markers or haplotypes initially found to be associating with the disease, as described herein. In other embodiments, the surrogate markers have RR or OR values greater than those initially determined for the markers initially found to be associating with the disease, as described herein. An example of such an embodiment would be a rare, or relatively rare (such as <10% allelic population frequency) variant in LD with a more common variant (>10% population frequency) initially found to be associating with the disease, such as the variants described herein. Identifying and using such markers for detecting the association discovered by the inventors as described herein can be performed by routine methods well known to the person skilled in the art, and are therefore within the scope of the present invention.

Determination of Haplotype Frequency

The frequencies of haplotypes in patient and control groups can be estimated using an expectation-maximization algorithm (Dempster A. et al., J. R. Stat. Soc. B, 39:1-38 (1977)). An implementation of this algorithm that can handle missing genotypes and uncertainty with the phase can be used. Under the null hypothesis, the patients and the controls are assumed to have identical frequencies. Using a likelihood approach, an alternative hypothesis is tested, where a candidate at-risk-haplotype, which can include the markers described herein, is allowed to have a higher frequency in patients than controls, while the ratios of the frequencies of other haplotypes are assumed to be the same in both groups. Likelihoods are maximized separately under both hypotheses and a corresponding 1-df likelihood ratio statistic is used to evaluate the statistical significance.

To look for at-risk and protective markers and haplotypes within a linkage region, for example, association of all possible combinations of genotyped markers is studied, provided those markers span a practical region. The combined patient and control groups can be randomly divided into two sets, equal in size to the original group of patients and controls. The marker and haplotype analysis is then repeated and the most significant p-value registered is determined. This randomization scheme can be repeated, for example, over 100 times to construct an empirical distribution of p-values. In a preferred embodiment, a p-value of <0.05 is indicative of a significant marker and/or haplotype association.

Haplotype Analysis

One general approach to haplotype analysis involves using likelihood-based inference applied to NEsted MOdels (Gretarsdottir S., et al., Nat. Genet. 35:131-38 (2003)). The method is implemented in the program NEMO, which allows for many polymorphic markers, SNPs and microsatellites. The method and software are specifically designed for case-control studies where the purpose is to identify haplotype groups that confer different risks. It is also a tool for studying LD structures. In NEMO, maximum likelihood estimates, likelihood ratios and p-values are calculated directly, with the aid of the EM algorithm, for the observed data treating it as a missing-data problem.

Even though likelihood ratio tests based on likelihoods computed directly for the observed data, which have captured the information loss due to uncertainty in phase and missing genotypes, can be relied on to give valid p-values, it would still be of interest to know how much information had been lost due to the information being incomplete. The information measure for haplotype analysis is described in Nicolae and Kong (Technical Report 537, Department of Statistics, University of Statistics, University of Chicago; Biometrics, 60(2):368-75 (2004)) as a natural extension of information measures defined for linkage analysis, and is implemented in NEMO.

For single marker association to a disease, the Fisher exact test can be used to calculate two-sided p-values for each individual allele. Usually, all p-values are presented unadjusted for multiple comparisons unless specifically indicated. The presented frequencies (for microsatellites, SNPs and haplotypes) are allelic frequencies as opposed to carrier frequencies. To minimize any bias due to the relatedness of patients who were recruited as families, first and second-degree relatives can be eliminated from the patient list. Furthermore, the test can be repeated for association correcting for any remaining relatedness among the patients, by extending a variance adjustment procedure described in Risch, N. & Teng, J. (Genome Res., 8:1273-1288 (1998)), DNA pooling (ibid) for sibships so that it can be applied to general familial relationships, and present both adjusted and unadjusted p-values for comparison. The differences are in general very small as expected. To assess the significance of single-marker association corrected for multiple testing we can carry out a randomization test using the same genotype data. Cohorts of patients and controls can be randomized and the association analysis redone multiple times (e.g., up to 500,000 times) and the p-value is the fraction of replications that produced a p-value for some marker allele that is lower than or equal to the p-value we observed using the original patient and control cohorts.

For both single-marker and haplotype analyses, relative risk (RR) and the population attributable risk (PAR) can be calculated assuming a multiplicative model (haplotype relative risk model) (Terwilliger, J. D. & Ott, J., Hum. Hered. 42:337-46 (1992) and Falk, C. T. & Rubinstein, P, Ann. Hum. Genet. 51 (Pt 3):227-33 (1987)), i.e., that the risks of the two alleles/haplotypes a person carries multiply. For example, if RR is the risk of A relative to a, then the risk of a person homozygote AA will be RR times that of a heterozygote Aa and RR² times that of a homozygote aa. The multiplicative model has a nice property that simplifies analysis and computations—haplotypes are independent, i.e., in Hardy-Weinberg equilibrium, within the affected population as well as within the control population. As a consequence, haplotype counts of the affecteds and controls each have multinomial distributions, but with different haplotype frequencies under the alternative hypothesis. Specifically, for two haplotypes, h_(i) and h_(j), risk(h_(i))/risk(h_(j))=(f_(i)/p_(i))/(f_(j)/p_(j)), where f and p denote, respectively, frequencies in the affected population and in the control population. While there is some power loss if the true model is not multiplicative, the loss tends to be mild except for extreme cases. Most importantly, p-values are always valid since they are computed with respect to null hypothesis.

An association signal detected in one association study may be replicated in a second cohort, ideally from a different population (e.g., different region of same country, or a different country) of the same or different ethnicity. The advantage of replication studies is that the number of tests performed in the replication study is usually quite small, and hence the less stringent the statistical measure that needs to be applied. For example, for a genome-wide search for susceptibility variants for a particular disease or trait using 300,000 SNPs, a correction for the 300,000 tests performed (one for each SNP) can be performed. Since many SNPs on the arrays typically used are correlated (i.e., in LD), they are not independent. Thus, the correction is conservative. Nevertheless, applying this correction factor requires an observed P-value of less than 0.05/300,000=1.7×10⁻⁷ for the signal to be considered significant applying this conservative test on results from a single study cohort. Obviously, signals found in a genome-wide association study with P-values less than this conservative threshold are a measure of a true genetic effect, and replication in additional cohorts is not necessarily from a statistical point of view. Importantly, however, signals with P-values that are greater than this threshold may also be due to a true genetic effect. Thus, since the correction factor depends on the number of statistical tests performed, if one signal (one SNP) from an initial study is replicated in a second case-control cohort, the appropriate statistical test for significance is that for a single statistical test, i.e., P-value less than 0.05. Replication studies in one or even several additional case-control cohorts have the added advantage of providing assessment of the association signal in additional populations, thus simultaneously confirming the initial finding and providing an assessment of the overall significance of the genetic variant(s) being tested in human populations in general.

The results from several case-control cohorts can also be combined to provide an overall assessment of the underlying effect. The methodology commonly used to combine results from multiple genetic association studies is the Mantel-Haenszel model (Mantel and Haenszel, J Natl Cancer Inst 22:719-48 (1959)). The model is designed to deal with the situation where association results from different populations, with each possibly having a different population frequency of the genetic variant, are combined. The model combines the results assuming that the effect of the variant on the risk of the disease, a measured by the OR or RR, is the same in all populations, while the frequency of the variant may differ between the populations. Combining the results from several populations has the added advantage that the overall power to detect a real underlying association signal is increased, due to the increased statistical power provided by the combined cohorts. Furthermore, any deficiencies in individual studies, for example due to unequal matching of cases and controls or population stratification will tend to balance out when results from multiple cohorts are combined, again providing a better estimate of the true underlying genetic effect.

Risk Assessment and Diagnostics

Within any given population, there is an absolute risk of developing a disease or trait, defined as the chance of a person developing the specific disease or trait over a specified time-period. For example, a woman's lifetime absolute risk of breast cancer is one in nine. That is to say, one woman in every nine will develop breast cancer at some point in their lives. Risk is typically measured by looking at very large numbers of people, rather than at a particular individual. Risk is often presented in terms of Absolute Risk (AR) and Relative Risk (RR). Relative Risk is used to compare risks associating with two variants or the risks of two different groups of people. For example, it can be used to compare a group of people with a certain genotype with another group having a different genotype. For a disease, a relative risk of 2 means that one group has twice the chance of developing a disease as the other group. The risk presented is usually the relative risk for a person, or a specific genotype of a person, compared to the population with matched gender and ethnicity. Risks of two individuals of the same gender and ethnicity could be compared in a simple manner. For example, if, compared to the population, the first individual has relative risk 1.5 and the second has relative risk 0.5, then the risk of the first individual compared to the second individual is 1.5/0.5=3.

As described herein, certain polymorphic markers and haplotypes comprising such markers are found to be useful for risk assessment of prostate cancer and colorectal cancer. Risk assessment can involve the use of the markers for diagnosing a susceptibility to prostate cancer and/or colorectal cancer. Particular alleles of polymorphic markers are found more frequently in individuals with prostate cancer and/or colorectal cancer, than in individuals without diagnosis of prostate cancer and/or colorectal cancer. Therefore, these marker alleles have predictive value for detecting prostate cancer and/or colorectal cancer, or a susceptibility to prostate cancer and/or colorectal cancer, in an individual. Tagging markers in linkage disequilibrium with the at-risk variants (or protective variants) described herein can be used as surrogates for these markers (and/or haplotypes). Such surrogate markers can be located within a particular haplotype block or LD block, e.g. LD Block C11 or LD Block C06. Such surrogate markers can also sometimes be located outside the physical boundaries of such a haplotype block or LD block, either in close vicinity of the LD block/haplotype block, but possibly also located in a more distant genomic location.

Long-distance LD can for example arise if particular genomic regions (e.g., genes) are in a functional relationship. For example, if two genes encode proteins that play a role in a shared metabolic pathway, then particular variants in one gene may have a direct impact on observed variants for the other gene. Let us consider the case where a variant in one gene leads to increased expression of the gene product. To counteract this effect and preserve overall flux of the particular pathway, this variant may have led to selection of one (or more) variants at a second gene that confers decreased expression levels of that gene. These two genes may be located in different genomic locations, possibly on different chromosomes, but variants within the genes are in apparent LD, not because of their shared physical location within a region of high LD, but rather due to evolutionary forces. Such LD is also contemplated and within scope of the present invention. The skilled person will appreciate that many other scenarios of functional gene-gene interaction are possible, and the particular example discussed here represents only one such possible scenario.

Markers with values of r² equal to 1 are perfect surrogates for the at-risk variants, i.e. genotypes for one marker perfectly predicts genotypes for the other. Markers with smaller values of r² than 1 can also be surrogates for the at-risk variant, or alternatively represent variants with relative risk values as high as or possibly even higher than the at-risk variant. The at-risk variant identified may not be the functional variant itself, but is in this instance in linkage disequilibrium with the true functional variant. The functional variant may for example be a tandem repeat, such as a minisatellite or a microsatellite, a transposable element (e.g., an Alu element), or a structural alteration, such as a deletion, insertion or inversion (sometimes also called copy number variations, or CNVs). The present invention encompasses the assessment of such surrogate markers for the markers as disclosed herein. Such markers are annotated, mapped and listed in public databases, as well known to the skilled person, or can alternatively be readily identified by sequencing the region or a part of the region identified by the markers of the present invention in a group of individuals, and identify polymorphisms in the resulting group of sequences. As a consequence, the person skilled in the art can readily and without undue experimentation genotype surrogate markers in linkage disequilibrium with the markers and/or haplotypes as described herein. The tagging or surrogate markers in LD with the at-risk variants detected, also have predictive value for detecting association to prostate cancer and/or colorectal cancer, or a susceptibility to prostate cancer and/or colorectal cancer, in an individual. These tagging or surrogate markers that are in LD with the markers of the present invention can also include other markers that distinguish among haplotypes, as these similarly have predictive value for detecting susceptibility to prostate cancer and/or colorectal cancer.

The present invention can in certain embodiments be practiced by assessing a sample comprising genomic DNA from an individual for the presence of variants described herein to be associated with cancer. Such assessment typically steps that detect the presence or absence of at least one allele of at least one polymorphic marker, using methods well known to the skilled person and further described herein, and based on the outcome of such assessment, determine whether the individual from whom the sample is derived is at increased or decreased risk (increased or decreased susceptibility) of cancer. Detecting particular alleles of polymorphic markers can in certain embodiments be done by obtaining nucleic acid sequence data for a particular human individual, that identifies at least one allele of at least one polymorphic marker. Different alleles of the at least one marker are associated with different susceptibility to the disease in humans. Obtaining nucleic acid sequence data can comprise nucleic acid sequence at a single nucleotide position, which is sufficient to identify alleles at polymorphic markers, such as SNPs and microsatellites. The nucleic acid sequence data can also comprise sequence at any other number of nucleotide positions, in particular for genetic markers that comprise multiple nucleotide positions, and can be anywhere from two to hundreds of thousands, possibly even millions, of nucleotides (in particular, in the case of copy number variations (CNVs)).

In certain embodiments, the invention can be practiced utilizing a dataset comprising information about the genotype status of at least one polymorphic marker associated with prostate and/or colorectal cancer (or markers in linkage disequilibrium with at least one marker associated with these diseases). In other words, a dataset containing information about such genetic status, for example in the form of genotype counts at a certain polymorphic marker, or a plurality of markers (e.g., an indication of the presence or absence of certain at-risk alleles), or actual genotypes for one or more markers, can be queried for the presence or absence of certain at-risk alleles at certain polymorphic markers shown by the present inventors to be associated with risk of prostate cancer and colorectal cancer. A positive result for a variant (e.g., marker allele) associated with the cancer is indicative of the individual from which the dataset is derived is at increased susceptibility (increased risk) of the cancer.

In certain embodiments of the invention, a polymorphic marker is correlated to the cancer by referencing genotype data for the polymorphic marker to a look-up table that comprises correlations between at least one allele of the polymorphism and the cancer. In some embodiments, the table comprises a correlation for one polymorphism. In other embodiments, the table comprises a correlation for a plurality of polymorphisms. In both scenarios, by referencing to a look-up table that gives an indication of a correlation between a marker and the cancer, a risk for the cancer, or a susceptibility to the cancer, can be identified in the individual from whom the sample is derived. In some embodiments, the correlation is reported as a statistical measure. The statistical measure may be reported as a risk measure, such as a relative risk (RR), an absolute risk (AR) or an odds ratio (OR).

The markers of the invention, e.g., the markers presented in Tables 1-6, may be useful for risk assessment and diagnostic purposes for prostate cancer and/or colorectal cancer, either alone or in combination. Thus, even in cases where the increase in risk by individual markers is relatively modest, i.e. on the order of 10-30%, the association may have significant implications. Thus, relatively common variants may have significant contribution to the overall risk (Population Attributable Risk is high), or combination of markers can be used to define groups of individual who, based on the combined risk of the markers, is at significant combined risk of developing the disease.

Thus, in one embodiment of the invention, a plurality of variants (genetic markers, biomarkers and/or haplotypes) is used for overall risk assessment. These variants are in one embodiment selected from the variants as disclosed herein. Other embodiments include the use of the variants of the present invention in combination with other variants known to be useful for diagnosing a susceptibility to prostate cancer and/or colorectal cancer. In such embodiments, the genotype status of a plurality of markers and/or haplotypes is determined in an individual, and the status of the individual compared with the population frequency of the associated variants, or the frequency of the variants in clinically healthy subjects, such as age-matched and sex-matched subjects. Methods known in the art, such as multivariate analyses or joint risk analyses, may subsequently be used to determine the overall risk conferred based on the genotype status at the multiple loci. Assessment of risk based on such analysis may subsequently be used in the methods and kits of the invention, as described herein.

In certain embodiments of risk assessment of prostate cancer, the variants described herein to be associated with prostate cancer risk are assessed in combination with at least one marker selected from the group consisting of rs2710646, rs 16901979, rs1447295, rs6983267, rs10896450, rs1859962, rs4430796 and rs5945572. Any combination of these markers, or surrogate markers in linkage disequilibrium therewith, with any of the variants described herein for risk assessment of prostate cancer is contemplated.

As described in the above, the haplotype block structure of the human genome has the effect that a large number of variants (markers and/or haplotypes) in linkage disequilibrium with the variant originally associated with a disease or trait may be used as surrogate markers for assessing association to the disease or trait. The number of such surrogate markers will depend on factors such as the historical recombination rate in the region, the mutational frequency in the region (i.e., the number of polymorphic sites or markers in the region), and the extent of LD (size of the LD block) in the region. These markers are usually located within the physical boundaries of the LD block or haplotype block in question as defined using the methods described herein (e.g., LD block C11 and/or LD block C06), or by other methods known to the person skilled in the art. However, sometimes marker and haplotype association is found to extend beyond the physical boundaries of the haplotype block as defined. Such markers and/or haplotypes may in those cases be also used as surrogate markers and/or haplotypes for the markers and/or haplotypes physically residing within the haplotype block as defined. As a consequence, markers and haplotypes in LD (typically characterized by r² greater than 0.1, such as r² greater than 0.2, including r² greater than 0.3, also including r² greater than 0.4) with the markers and haplotypes of the present invention are also within the scope of the invention, even if they are physically located beyond the boundaries of the haplotype block as defined. This includes markers that are described herein (e.g., Tables 1-6, e.g. Tables 3-4), but may also include other markers that are in strong LD (e.g., characterized by r² greater than 0.1 or 0.2 and/or |D′|>0.8) with one or more of the markers listed in Tables 1-6.

For the SNP markers described herein, the opposite allele to the allele found to be in excess in patients (at-risk allele) is found in decreased frequency in prostate cancer and/or colorectal cancer. These markers and haplotypes in LD and/or comprising such markers, are thus protective for prostate cancer and/or colorectal cancer, i.e. they confer a decreased risk or susceptibility of individuals carrying these markers and/or haplotypes developing prostate cancer and/or colorectal cancer.

Certain variants of the present invention, including certain haplotypes comprise, in some cases, a combination of various genetic markers, e.g., SNPs and microsatellites. Detecting haplotypes can be accomplished by methods known in the art and/or described herein for detecting sequences at polymorphic sites. Furthermore, correlation between certain haplotypes or sets of markers and disease phenotype can be verified using standard techniques. A representative example of a simple test for correlation would be a Fisher-exact test on a two by two table.

In specific embodiments, a marker allele or haplotype found to be associated with prostate cancer and/or colorectal cancer, (e.g., marker alleles as listed in Tables 1-6) is one in which the marker allele or haplotype is more frequently present in an individual at risk for prostate cancer and/or colorectal cancer (affected), compared to the frequency of its presence in a healthy individual (control), wherein the presence of the marker allele or haplotype is indicative of prostate cancer and/or colorectal cancer or a susceptibility to prostate cancer and/or colorectal cancer. In other embodiments, at-risk markers in linkage disequilibrium with one or more markers found to be associated with prostate cancer and/or colorectal cancer (e.g., marker alleles as listed in Tables 1-6) are tagging markers that are more frequently present in an individual at risk for prostate cancer and/or colorectal cancer (affected), compared to the frequency of their presence in a healthy individual (control), wherein the presence of the tagging markers is indicative of increased susceptibility to prostate cancer and/or colorectal cancer. In a further embodiment, at-risk markers alleles (i.e. conferring increased susceptibility) in linkage disequilibrium with one or more markers found to be associated with prostate cancer and/or colorectal cancer (e.g., marker alleles as listed in Table 1-6), are markers comprising one or more allele that is more frequently present in an individual at risk for prostate cancer and/or colorectal cancer, compared to the frequency of their presence in a healthy individual (control), wherein the presence of the markers is indicative of increased susceptibility to.

Study Population

In a general sense, the methods and kits of the invention can be utilized from samples containing genomic DNA from any source, i.e. any individual. In preferred embodiments, the individual is a human individual. The individual can be an adult, child, or fetus. The present invention also provides for assessing markers and/or haplotypes in individuals who are members of a target population. Such a target population is in one embodiment a population or group of individuals at risk of developing the disease, based on other genetic factors, biomarkers, biophysical parameters (e.g., weight, BMD, blood pressure), or general health and/or lifestyle parameters (e.g., history of prostate and/or colorectal cancer or other cancers, previous diagnosis of prostate and/or colorectal cancer, family history of prostate cancer and/or colorectal cancer).

The invention provides for embodiments that include individuals from specific age subgroups, such as those over the age of 40, over age of 45, or over age of 50, 55, 60, 65, 70, 75, 80, or 85. Other embodiments of the invention pertain to other age groups, such as individuals aged less than 85, such as less than age 80, less than age 75, or less than age 70, 65, 60, 55, 50, 45, 40, 35, or age 30. Other embodiments relate to individuals with age at onset of the disease in any of the age ranges described in the above. It is also contemplated that a range of ages may be relevant in certain embodiments, such as age at onset at more than age 45 but less than age 60. Other age ranges are however also contemplated, including all age ranges bracketed by the age values listed in the above. The invention furthermore relates to individuals of either gender, males or females.

The Icelandic population is a Caucasian population of Northern European ancestry. A large number of studies reporting results of genetic linkage and association in the Icelandic population have been published in the last few years. Many of those studies show replication of variants, originally identified in the Icelandic population as being associating with a particular disease, in other populations (Styrkarsdottir, U., et al. N Engl J Med Apr. 29 2008 (Epub ahead of print); Thorgeirsson, T., et al. Nature 452:638-42 (2008); Gudmundsson, J., et al. Nat Genet. 40:281-3 (2008); Stacey, S, N., et al., Nat Genet. 39:865-69 (2007); Helgadottir, A., et al., Science 316:1491-93 (2007); Steinthorsdottir, V., et al., Nat Genet. 39:770-75 (2007); Gudmundsson, J., et al., Nat Genet. 39:631-37 (2007); Frayling, T M, Nature Reviews Genet 8:657-662 (2007); Amundadottir, L. T., et al., Nat Genet. 38:652-58 (2006); Grant, S. F., et al., Nat Genet. 38:320-23 (2006)). Thus, genetic findings in the Icelandic population have in general been replicated in other populations, including populations from Africa and Asia.

It is thus believed that the markers of the present invention found to be associated with risk of prostate cancer and colorectal cancer to show similar association in other human populations. Particular embodiments comprising individual human populations are thus also contemplated and within the scope of the invention. Such embodiments relate to human subjects that are from one or more human population including, but not limited to, Caucasian populations, European populations, American populations, Eurasian populations, Asian populations, Central/South Asian populations, East Asian populations, Middle Eastern populations, African populations, Hispanic populations, and Oceanian populations. European populations include, but are not limited to, Swedish, Norwegian, Finnish, Russian, Danish, Icelandic, Irish, Kelt, English, Scottish, Dutch, Belgian, French, German, Spanish, Portugues, Italian, Polish, Bulgarian, Slavic, Serbian, Bosnian, Chech, Greek and Turkish populations. The invention furthermore in other embodiments can be practiced in specific human populations that include Bantu, Mandenk, Yoruba, San, Mbuti Pygmy, Orcadian, Adygel, Russian, Sardinian, Tuscan, Mozabite, Bedouin, Druze, Palestinian, Balochi, Brahui, Makrani, Sindhi, Pathan, Burusho, Hazara, Uygur, Kalash, Han, Dai, Daur, Hezhen, Lahu, Miao, Orogen, She, Tujia, Tu, Xibo, Yi, Mongolan, Naxi, Cambodian, Japanese, Yakut, Melanesian, Papuan, Karitianan, Surui, Colmbian, Maya and Pima.

In one preferred embodiment, the invention relates to populations that include black African ancestry such as populations comprising persons of African descent or lineage. Black African ancestry may be determined by self reporting as African-Americans, Afro-Americans, Black Americans, being a member of the black race or being a member of the negro race. For example, African Americans or Black Americans are those persons living in North America and having origins in any of the black racial groups of Africa. In another example, self-reported persons of black African ancestry may have at least one parent of black African ancestry or at least one grandparent of black African ancestry.

The racial contribution in individual subjects may also be determined by genetic analysis. Genetic analysis of ancestry may be carried out using unlinked microsatellite markers such as those set out in Smith et al. (Am J Hum Genet 74, 1001-13 (2004)).

In certain embodiments, the invention relates to markers and/or haplotypes identified in specific populations, as described in the above. The person skilled in the art will appreciate that measures of linkage disequilibrium (LD) may give different results when applied to different populations. This is due to different population history of different human populations as well as differential selective pressures that may have led to differences in LD in specific genomic regions. It is also well known to the person skilled in the art that certain markers, e.g. SNP markers, have different population frequency in different populations, or are polymorphic in one population but not in another. The person skilled in the art will however apply the methods available and as thought herein to practice the present invention in any given human population. This may include assessment of polymorphic markers in the LD region of the present invention, so as to identify those markers that give strongest association within the specific population. Thus, the at-risk variants of the present invention may reside on different haplotype background and in different frequencies in various human populations. However, utilizing methods known in the art and the markers of the present invention, the invention can be practiced in any given human population.

Utility of Genetic Testing

The person skilled in the art will appreciate and understand that the variants described herein in general do not, by themselves, provide an absolute identification of individuals who will develop a particular disease. The variants described herein do however indicate increased and/or decreased likelihood that individuals carrying the at-risk or protective variants of the invention will develop symptoms associated with prostate cancer and/or colorectal cancer. This information is however extremely valuable in itself, as outlined in more detail in the below, as it can be used to, for example, initiate preventive measures at an early stage, perform regular physical and/or mental exams to monitor the progress and/or appearance of symptoms, or to schedule exams at a regular interval to identify the condition in question, so as to be able to apply treatment at an early stage.

The knowledge of a genetic variant that confers a risk of developing cancer offers the opportunity to apply a genetic-test to distinguish between individuals with increased risk of developing the cancer (i.e. carriers of the at-risk variant) and those with decreased risk of developing the cancer (i.e. carriers of the protective variant, or non-carriers of the at-risk variant). The core values of genetic testing, for individuals belonging to both of the above mentioned groups, are the possibilities of being able to diagnose the cancer at an early stage and provide information to the clinician about prognosis/aggressiveness of the disease in order to be able to apply the most appropriate treatment. For example, the application of a genetic test for cancer (e.g., colorectal cancer or prostate cancer (including aggressive or high Gleason grade prostate cancer, less aggressive or low Gleason grade prostate cancer)) can provide an opportunity for the detection of the cancer at an earlier stage which may lead to the application of therapeutic measures at an earlier stage, and thus can minimize the deleterious effects of the symptoms and serious health consequences conferred by cancer. Some advantages of genetic tests for prostate cancer include:

1. To Aid Early Detection

The application of a genetic test for prostate cancer can provide an opportunity for the detection of the disease at an earlier stage which leads to higher cure rates, if found locally, and increases survival rates by minimizing regional and distant spread of the tumor. For prostate cancer, a genetic test will most likely increase the sensitivity and specificity of the already generally applied Prostate Specific Antigen (PSA) test and Digital Rectal Examination (DRE). This can lead to lower rates of false positives (thus minimize unnecessary procedures such as needle biopsies) and false negatives (thus increasing detection of occult disease and minimizing morbidity and mortality due to PCA).

2. To Determine Aggressiveness

Genetic testing can provide information about pre-diagnostic prognostic indicators and enable the identification of individuals at high or low risk for aggressive tumor types that can lead to modification in screening strategies. For example, an individual determined to be a carrier of a high risk allele for the development of aggressive prostate cancer will likely undergo more frequent PSA testing, examination and have a lower threshold for needle biopsy in the presence of an abnormal PSA value.

Furthermore, identifying individuals that are carriers of high or low risk alleles for aggressive tumor types will lead to modification in treatment strategies. For example, if prostate cancer is diagnosed in an individual that is a carrier of an allele that confers increased risk of developing an aggressive form of prostate cancer, then the clinician would likely advise a more aggressive treatment strategy such as a prostatectomy instead of a less aggressive treatment strategy.

As is known in the art, Prostate Specific Antigen (PSA) is a protein that is secreted by the epithelial cells of the prostate gland, including cancer cells. An elevated level in the blood indicates an abnormal condition of the prostate, either benign or malignant. PSA is used to detect potential problems in the prostate gland and to follow the progress of prostate cancer therapy. PSA levels above 4 ng/ml are indicative of the presence of prostate cancer (although as known in the art and described herein, the test is neither very specific nor sensitive).

In one embodiment, the method of the invention is performed in combination with (either prior to, concurrently or after) a PSA assay. In a particular embodiment, the presence of an at-risk marker or haplotype, in conjunction with the subject having a PSA level greater than 4 ng/ml, is indicative of a more aggressive prostate cancer and/or a worse prognosis. As described herein, particular markers and haplotypes are associated with high Gleason (i.e., more aggressive) prostate cancer. In another embodiment, the presence of a marker or haplotype, in a patient who has a normal PSA level (e.g., less than 4 ng/ml), is indicative of a high Gleason (i.e., more aggressive) prostate cancer and/or a worse prognosis. A “worse prognosis” or “bad prognosis” occurs when it is more likely that the cancer will grow beyond the boundaries of the prostate gland, metastasize, escape therapy and/or kill the host.

In one embodiment, the presence of a marker or haplotype is indicative of a predisposition to a somatic rearrangement (e.g., one or more of an amplification, a translocation, an insertion and/or deletion) in a tumor or its precursor. The somatic rearrangement itself may subsequently lead to a more aggressive form of prostate cancer (e.g., a higher histologic grade, as reflected by a higher Gleason score or higher stage at diagnosis, an increased progression of prostate cancer (e.g., to a higher stage), a worse outcome (e.g., in terms of morbidity, complications or death)). As is known in the art, the Gleason grade is a widely used method for classifying prostate cancer tissue for the degree of loss of the normal glandular architecture (size, shape and differentiation of glands). A grade from 1-5 is assigned successively to each of the two most predominant tissue patterns present in the examined tissue sample and are added together to produce the total or combined Gleason grade (scale of 2-10). High numbers indicate poor differentiation and therefore more aggressive cancer.

Aggressive prostate cancer is cancer that grows beyond the prostate, metastasizes and eventually kills the patient. As described herein, one surrogate measure of aggressiveness is a high combined Gleason grade. The higher the grade on a scale of 2-10 the more likely it is that a patient has aggressive disease.

The present invention furthermore relates to risk assessment for prostate cancer and colorectal cancer, including diagnosing whether an individual is at risk for developing prostate cancer and/or colorectal cancer. The polymorphic markers of the present invention can be used alone or in combination, as well as in combination with other factors, including other genetic risk factors or biomarkers, for risk assessment of an individual for prostate cancer and/or colorectal cancer. Certain factors known to affect the predisposition of an individual towards developing risk of developing common disease, including prostate cancer and/or colorectal cancer are known to the person skilled in the art and can be utilized in such assessment. These include, but are not limited to, age, gender, smoking status, family history of cancer, previously diagnosed cancer, colonic adenomas, chronic inflammatory bowel disease and diet. Methods known in the art can be used for such assessment, including multivariate analyses or logistic regression.

Methods

Methods for risk assessment of and risk management of prostate cancer and/or colorectal cancer are described herein and are encompassed by the invention. The invention also encompasses methods of assessing an individual for probability of response to a therapeutic agent for prostate cancer and/or colorectal cancer, as well as methods for predicting the effectiveness of a therapeutic agent for prostate cancer and/or colorectal cancer. Kits for assaying a sample from a subject to detect susceptibility to prostate cancer and/or colorectal cancer are also encompassed by the invention.

Diagnostic and Screening Methods

In certain embodiments, the present invention pertains to methods of diagnosing, or aiding in the diagnosis of, prostate cancer and/or colorectal cancer or a susceptibility to prostate cancer and/or colorectal cancer, by detecting particular alleles at genetic markers that appear more frequently in prostate cancer and/or colorectal cancer subjects or subjects who are susceptible to prostate cancer and/or colorectal cancer. In a particular embodiment, the invention is a method of diagnosing a susceptibility to prostate cancer and/or colorectal cancer by detecting at least one allele of at least one polymorphic marker (e.g., the markers described herein). The present invention describes methods whereby detection of particular alleles of particular markers or haplotypes is indicative of a susceptibility to prostate cancer and/or colorectal cancer. Such prognostic or predictive assays can also be used to determine prophylactic treatment of a subject prior to the onset of symptoms of prostate cancer and/or colorectal cancer.

The present invention pertains in some embodiments to methods of clinical applications of diagnosis, e.g., diagnosis performed by a medical professional. In other embodiments, the invention pertains to methods of diagnosis performed by a layman. The layman can be the customer of a genotyping service. The layman may also be a genotype service provider, who performs genotype analysis on a DNA sample from an individual, in order to provide service related to genetic risk factors for particular traits or diseases, based on the genotype status of the individual (i.e., the customer). Recent technological advances in genotyping technologies, including high-throughput genotyping of SNP markers, such as Molecular Inversion Probe array technology (e.g., Affymetrix GeneChip), and BeadArray Technologies (e.g., Illumina GoldenGate and Infinium assays) have made it possible for individuals to have their own genome assessed for up to one million SNPs simultaneously, at relatively little cost. The resulting genotype information, made available to the customer can be compared to information from the public literature about disease or trait risk associated with various SNPs. The diagnostic application of disease-associated alleles as described herein, can thus be performed either by the individual, through analysis of his/her genotype data, or by a health professional based on results of a clinical test. In other words, the diagnosis or assessment of a susceptibility based on genetic risk can be made by health professionals, genetic counselors or by the layman, based on information about his/her genotype and publications on various risk factors. In the present context, the term “diagnosing”, and “diagnose a susceptibility”, is meant to refer to any available diagnostic method, including those mentioned above.

In certain embodiments, a sample containing genomic DNA from an individual is collected. Such sample can for example be a buccal swab, a saliva sample, a blood sample, or other suitable samples containing genomic DNA, as described further herein. The genomic DNA is then analyzed using any common technique available to the skilled person, such as high-throughput array technologies. Results from such genotyping are stored in a convenient data storage unit, such as a data carrier, including computer databases, data storage disks, or by other convenient data storage means. In certain embodiments, the computer database is an object database, a relational database or a post-relational database. The genotype data is subsequently analyzed for the presence of certain variants known to be susceptibility variants for a particular human conditions, such as the genetic variants described herein. Genotype data can be retrieved from the data storage unit using any convenient data query method. Calculating risk conferred by a particular genotype for the individual can be based on comparing the genotype of the individual to previously determined risk (expressed as a relative risk (RR) or and odds ratio (OR), for example) for the genotype, for example for an heterozygous carrier of an at-risk variant for a particular disease or trait (such as prostate cancer and colorectal cancer). The calculated risk for the individual can be the relative risk for a person, or for a specific genotype of a person, compared to the average population with matched gender and ethnicity. The average population risk can be expressed as a weighted average of the risks of different genotypes, using results from a reference population, and the appropriate calculations to calculate the risk of a genotype group relative to the population can then be performed. Alternatively, the risk for an individual is based on a comparison of particular genotypes, for example heterozygous carriers of an at-risk allele of a marker compared with non-carriers of the at-risk allele. Using the population average may in certain embodiments be more convenient, since it provides a measure which is easy to interpret for the user, i.e. a measure that gives the risk for the individual, based on his/her genotype, compared with the average in the population. The calculated risk estimated can be made available to the customer via a website, preferably a secure website.

In certain embodiments, a service provider will include in the provided service all of the steps of isolating genomic DNA from a sample provided by the customer, performing genotyping of the isolated DNA, calculating genetic risk based on the genotype data, and report the risk to the customer. In some other embodiments, the service provider will include in the service the interpretation of genotype data for the individual, i.e., risk estimates for particular genetic variants based on the genotype data for the individual. In some other embodiments, the service provider may include service that includes genotyping service and interpretation of the genotype data, starting from a sample of isolated DNA from the individual (the customer).

Custom sequencing service can also be used to assess genotype status of individuals. Targeted sequencing or whole genome sequencing technologies can be used to determine the identity of nucleotides at certain polymorphic sites. Determination of such identity defines the allelic status of the individual at the site, i.e. provides genotype information. Such sequencing services can thus also be utilized to realize the present invention. As whole-genome sequencing technologies become economically feasible on a large scale, utilization of genotype information based on such technologies may become preferable. Certain embodiments of the invention encompass genotyping performed by such sequencing technologies.

In addition, in certain other embodiments, the present invention pertains to methods of diagnosing, or aiding in the diagnosis of, a decreased susceptibility to prostate cancer and/or colorectal cancer, by detecting particular genetic marker alleles or haplotypes that appear less frequently in prostate cancer and/or colorectal cancer patients than in individual not diagnosed with prostate cancer and/or colorectal cancer or in the general population.

Overall risk for multiple risk variants can be performed using standard methodology. For example, assuming a multiplicative model, i.e. assuming that the risk of individual risk variants multiply to establish the overall effect, allows for a straightforward calculation of the overall risk for multiple markers.

As described and exemplified herein, particular marker alleles or haplotypes (e.g. the markers and haplotypes as listed in Tables 1-6) are associated with prostate cancer and colorectal cancer. In one embodiment, the marker allele or haplotype is one that confers a significant risk or susceptibility to prostate cancer and/or colorectal cancer. In another embodiment, the invention relates to a method of determining or diagnosing a susceptibility to prostate cancer and/or colorectal cancer in a human individual, the method comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, wherein the at least one polymorphic marker is selected from the group consisting of the polymorphic markers listed in Table 5 and 6, and markers in linkage disequilibrium (e.g., defined as r²>0.2) therewith. In another embodiment, the invention pertains to methods of diagnosing or determining a susceptibility to prostate cancer and/or colorectal cancer in a human individual, by screening for at least one marker allele as listed in Table 3 and Table 4 or markers in linkage disequilibrium therewith. In another embodiment, the invention relates to methods of diagnosing or determining a susceptibility to colorectal cancer in a human individual, by screening for at least one marker as listed in Table 4. In another embodiment, the marker allele or haplotype is more frequently present in a subject having, or who is susceptible to, prostate cancer and/or colorectal cancer (affected), as compared to the frequency of its presence in a healthy subject (control, such as population controls). In certain embodiments, the significance of association of the at least one marker allele or haplotype is characterized by a p value <0.05. In other embodiments, the significance of association is characterized by smaller p-values, such as <0.01, <0.001, <0.0001, <0.00001, <0.000001, <0.0000001, <0.00000001 or <0.000000001.

In these embodiments, the presence of the at least one marker allele or haplotype is indicative of a susceptibility to prostate cancer and/or colorectal cancer. These diagnostic methods involve detecting the presence or absence of at least one marker allele or haplotype that is associated with prostate cancer and/or colorectal cancer. The haplotypes described herein include combinations of alleles at various genetic markers (e.g., SNPs, microsatellites). The detection of the particular genetic marker alleles that make up the particular haplotypes can be performed by a variety of methods described herein and/or known in the art. For example, genetic markers can be detected at the nucleic acid level (e.g., by direct nucleotide sequencing or by other means known to the skilled in the art) or at the amino acid level if the genetic marker affects the coding sequence of a protein encoded by a cancer (prostate cancer or colorectal cancer)-associated nucleic acid (e.g., by protein sequencing or by immunoassays using antibodies that recognize such a protein). The marker alleles or haplotypes of the present invention correspond to fragments of a genomic DNA sequence associated with prostate cancer and/or colorectal cancer. Such fragments encompass the DNA sequence of the polymorphic marker or haplotype in question, but may also include DNA segments in strong LD (linkage disequilibrium) with the marker or haplotype. In one embodiment, such segments comprises segments in LD with the marker or haplotype as determined by a value of r² greater than 0.1 and/or |D′|>0.8).

In one embodiment, diagnosis of a susceptibility to prostate cancer and/or colorectal cancer can be accomplished using hybridization methods, such as Southern analysis, Northern analysis, and/or in situ hybridizations (see Current Protocols in Molecular Biology, Ausubel, F. et al., eds., John Wiley & Sons, including all supplements). The presence of a specific marker allele can be indicated by sequence-specific hybridization of a nucleic acid probe specific for the particular allele. The presence of more than specific marker allele or a specific haplotype can be indicated by using several sequence-specific nucleic acid probes, each being specific for a particular allele. In one embodiment, a haplotype can be indicated by a single nucleic acid probe that is specific for the specific haplotype (i.e., hybridizes specifically to a DNA strand comprising the specific marker alleles characteristic of the haplotype). A sequence-specific probe can be directed to hybridize to genomic DNA, RNA, or cDNA. A “nucleic acid probe”, as used herein, can be a DNA probe or an RNA probe that hybridizes to a complementary sequence. One of skill in the art would know how to design such a probe so that sequence specific hybridization will occur only if a particular allele is present in a genomic sequence from a test sample.

To diagnose a susceptibility to prostate cancer and/or colorectal cancer, a hybridization sample is formed by contacting the test sample containing a prostate cancer and/or colorectal cancer-associated nucleic acid, such as a genomic DNA sample, with at least one nucleic acid probe. A non-limiting example of a probe for detecting mRNA or genomic DNA is a labeled nucleic acid probe that is capable of hybridizing to mRNA or genomic DNA sequences described herein. The nucleic acid probe can be, for example, a full-length nucleic acid molecule, or a portion thereof, such as an oligonucleotide of at least 15, 30, 50, 100, 250 or 500 nucleotides in length that is sufficient to specifically hybridize under stringent conditions to appropriate mRNA or genomic DNA. For example, the nucleic acid probe can comprise all or a portion of the nucleotide sequence of LD Block C06 or LD Block C11, as described herein, optionally comprising at least one allele of a marker described herein, or the probe can be the complementary sequence of such a sequence. In a particular embodiment, the nucleic acid probe is a portion of the nucleotide sequence of LD Block C06 or LD Block C11, as described herein, optionally comprising at least one allele of a marker described herein, or at least one allele of one polymorphic marker or haplotype comprising at least one polymorphic marker described herein, or the probe can be the complementary sequence of such a sequence. Other suitable probes for use in the diagnostic assays of the invention are described herein. Hybridization can be performed by methods well known to the person skilled in the art (see, e.g., Current Protocols in Molecular Biology, Ausubel, F. et al., eds., John Wiley & Sons, including all supplements). In one embodiment, hybridization refers to specific hybridization, i.e., hybridization with no mismatches (exact hybridization). In one embodiment, the hybridization conditions for specific hybridization are high stringency.

Specific hybridization, if present, is detected using standard methods. If specific hybridization occurs between the nucleic acid probe and the nucleic acid in the test sample, then the sample contains the allele that is complementary to the nucleotide that is present in the nucleic acid probe. The process can be repeated for any markers of the present invention, or markers that make up a haplotype of the present invention, or multiple probes can be used concurrently to detect more than one, marker alleles at a time. It is also possible to design a single probe containing more than one marker alleles of a particular haplotype (e.g., a probe containing alleles complementary to 2, 3, 4, 5 or all of the markers that make up a particular haplotype). Detection of the particular markers of the haplotype in the sample is indicative that the source of the sample has the particular haplotype (e.g., a haplotype) and therefore is susceptible to prostate cancer and/or colorectal cancer.

In one preferred embodiment, a method utilizing a detection oligonucleotide probe comprising a fluorescent moiety or group at its 3′ terminus and a quencher at its 5′ terminus, and an enhancer oligonucleotide, is employed, as described by Kutyavin et al. (Nucleic Acid Res. 34:e128 (2006)). The fluorescent moiety can be Gig Harbor Green or Yakima Yellow, or other suitable fluorescent moieties. The detection probe is designed to hybridize to a short nucleotide sequence that includes the SNP polymorphism to be detected. Preferably, the SNP is anywhere from the terminal residue to −6 residues from the 3′ end of the detection probe. The enhancer is a short oligonucleotide probe which hybridizes to the DNA template 3′ relative to the detection probe. The probes are designed such that a single nucleotide gap exists between the detection probe and the enhancer nucleotide probe when both are bound to the template. The gap creates a synthetic abasic site that is recognized by an endonuclease, such as Endonuclease IV. The enzyme cleaves the dye off the fully complementary detection probe, but cannot cleave a detection probe containing a mismatch. Thus, by measuring the fluorescence of the released fluorescent moiety, assessment of the presence of a particular allele defined by nucleotide sequence of the detection probe can be performed.

The detection probe can be of any suitable size, although preferably the probe is relatively short. In one embodiment, the probe is from 5-100 nucleotides in length. In another embodiment, the probe is from 10-50 nucleotides in length, and in another embodiment, the probe is from 12-30 nucleotides in length. Other lengths of the probe are possible and within scope of the skill of the average person skilled in the art.

In a preferred embodiment, the DNA template containing the SNP polymorphism is amplified by Polymerase Chain Reaction (PCR) prior to detection. In such an embodiment, the amplified DNA serves as the template for the detection probe and the enhancer probe.

Certain embodiments of the detection probe, the enhancer probe, and/or the primers used for amplification of the template by PCR include the use of modified bases, including modified A and modified G. The use of modified bases can be useful for adjusting the melting temperature of the nucleotide molecule (probe and/or primer) to the template DNA, for example for increasing the melting temperature in regions containing a low percentage of G or C bases, in which modified A with the capability of forming three hydrogen bonds to its complementary T can be used, or for decreasing the melting temperature in regions containing a high percentage of G or C bases, for example by using modified G bases that form only two hydrogen bonds to their complementary C base in a double stranded DNA molecule. In a preferred embodiment, modified bases are used in the design of the detection nucleotide probe. Any modified base known to the skilled person can be selected in these methods, and the selection of suitable bases is well within the scope of the skilled person based on the teachings herein and known bases available from commercial sources as known to the skilled person.

In another hybridization method, Northern analysis (see Current Protocols in Molecular Biology, Ausubel, F. et al., eds., John Wiley & Sons, supra) is used to identify the presence of a polymorphism associated with prostate cancer and/or colorectal cancer. For Northern analysis, a test sample of RNA is obtained from the subject by appropriate means. As described herein, specific hybridization of a nucleic acid probe to RNA from the subject is indicative of a particular allele complementary to the probe. For representative examples of use of nucleic acid probes, see, for example, U.S. Pat. Nos. 5,288,611 and 4,851,330.

Additionally, or alternatively, a peptide nucleic acid (PNA) probe can be used in addition to, or instead of, a nucleic acid probe in the hybridization methods described herein. A PNA is a DNA mimic having a peptide-like, inorganic backbone, such as N-(2-aminoethyl)glycine units, with an organic base (A, G, C, T or U) attached to the glycine nitrogen via a methylene carbonyl linker (see, for example, Nielsen, P., et al., Bioconjug. Chem. 5:3-7 (1994)). The PNA probe can be designed to specifically hybridize to a molecule in a sample suspected of containing one or more of the marker alleles or haplotypes that are associated with prostate cancer and/or colorectal cancer. Hybridization of the PNA probe is thus diagnostic for prostate cancer and/or colorectal cancer or a susceptibility to prostate cancer and/or colorectal cancer

In one embodiment of the invention, a test sample containing genomic DNA obtained from the subject is collected and the polymerase chain reaction (PCR) is used to amplify a fragment comprising one or more markers or haplotypes of the present invention. As described herein, identification of a particular marker allele or haplotype associated with prostate cancer and/or colorectal cancer, can be accomplished using a variety of methods (e.g., sequence analysis, analysis by restriction digestion, specific hybridization, single stranded conformation polymorphism assays (SSCP), electrophoretic analysis, etc.). In another embodiment, diagnosis is accomplished by expression analysis using quantitative PCR (kinetic thermal cycling). This technique can, for example, utilize commercially available technologies, such as TaqMan® (Applied Biosystems, Foster City, Calif.). The technique can assess the presence of an alteration in the expression or composition of a polypeptide or splicing variant(s) that is encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer. Further, the expression of the variant(s) can be quantified as physically or functionally different.

In another embodiment of the methods of the invention, analysis by restriction digestion can be used to detect a particular allele if the allele results in the creation or elimination of a restriction site relative to a reference sequence. Restriction fragment length polymorphism (RFLP) analysis can be conducted, e.g., as described in Current Protocols in Molecular Biology, supra. The digestion pattern of the relevant DNA fragment indicates the presence or absence of the particular allele in the sample.

Sequence analysis can also be used to detect specific alleles or haplotypes associated with prostate cancer and/or colorectal cancer (e.g. the polymorphic markers of Tables 4 and 5, and markers in linkage disequilibrium therewith). Therefore, in one embodiment, determination of the presence or absence of a particular marker alleles or haplotypes comprises sequence analysis of a test sample of DNA or RNA obtained from a subject or individual. PCR or other appropriate methods can be used to amplify a portion of a nucleic acid associated with prostate cancer and/or colorectal cancer, and the presence of a specific allele can then be detected directly by sequencing the polymorphic site (or multiple polymorphic sites in a haplotype) of the genomic DNA in the sample.

Allele-specific oligonucleotides can also be used to detect the presence of a particular allele in a nucleic acid associated with prostate cancer and/or colorectal cancer (e.g. the polymorphic markers of Tables 3 and 4, and markers in linkage disequilibrium therewith), through the use of dot-blot hybridization of amplified oligonucleotides with allele-specific oligonucleotide (ASO) probes (see, for example, Saiki, R. et al., Nature, 324:163-166 (1986)). An “allele-specific oligonucleotide” (also referred to herein as an “allele-specific oligonucleotide probe”) is an oligonucleotide of approximately 10-50 base pairs or approximately 15-30 base pairs, that specifically hybridizes to a nucleic acid associated with prostate cancer and/or colorectal cancer, and which contains a specific allele at a polymorphic site (e.g., a marker or haplotype as described herein). An allele-specific oligonucleotide probe that is specific for one or more particular a nucleic acid associated with prostate cancer and/or colorectal cancer can be prepared using standard methods (see, e.g., Current Protocols in Molecular Biology, supra). PCR can be used to amplify the desired region. The DNA containing the amplified region can be dot-blotted using standard methods (see, e.g., Current Protocols in Molecular Biology, supra), and the blot can be contacted with the oligonucleotide probe. The presence of specific hybridization of the probe to the amplified region can then be detected. Specific hybridization of an allele-specific oligonucleotide probe to DNA from the subject is indicative of a specific allele at a polymorphic site associated with DISEASE (see, e.g., Gibbs, R. et al., Nucleic Acids Res., 17:2437-2448 (1989) and WO 93/22456).

In another embodiment, arrays of oligonucleotide probes that are complementary to target nucleic acid sequence segments from a subject, can be used to identify particular alleles at polymorphic sites. For example, an oligonucleotide array can be used. Oligonucleotide arrays typically comprise a plurality of different oligonucleotide probes that are coupled to a surface of a substrate in different known locations. These arrays can generally be produced using mechanical synthesis methods or light directed synthesis methods that incorporate a combination of photolithographic methods and solid phase oligonucleotide synthesis methods, or by other methods known to the person skilled in the art (see, e.g., Bier, F. F., et al. Adv Biochem Eng Biotechnol 109:433-53 (2008); Hoheisel, J. D., Nat Rev Genet 7:200-10 (2006); Fan, J. B., et al. Methods Enzymol 410:57-73 (2006); Raqoussis, J. & Elvidge, G., Expert Rev Mol Diagn 6:145-52 (2006); Mockler, T. C., et al Genomics 85:1-15 (2005), and references cited therein, the entire teachings of each of which are incorporated by reference herein). Many additional descriptions of the preparation and use of oligonucleotide arrays for detection of polymorphisms can be found, for example, in U.S. Pat. No. 6,858,394, U.S. Pat. No. 6,429,027, U.S. Pat. No. 5,445,934, U.S. Pat. No. 5,700,637, U.S. Pat. No. 5,744,305, U.S. Pat. No. 5,945,334, U.S. Pat. No. 6,054,270, U.S. Pat. No. 6,300,063, U.S. Pat. No. 6,733,977, U.S. Pat. No. 7,364,858, EP 619 321, and EP 373 203, the entire teachings of which are incorporated by reference herein.

Other methods of nucleic acid analysis that are available to those skilled in the art can be used to detect a particular allele at a polymorphic site associated with prostate cancer and/or colorectal cancer (e.g. the polymorphic markers of Tables 3 and 4, and markers in linkage disequilibrium therewith). Representative methods include, for example, direct manual sequencing (Church and Gilbert, Proc. Natl. Acad. Sci. USA, 81: 1991-1995 (1988); Sanger, F., et al., Proc. Natl. Acad. Sci. USA, 74:5463-5467 (1977); Beavis, et al., U.S. Pat. No. 5,288,644); automated fluorescent sequencing; single-stranded conformation polymorphism assays (SSCP); clamped denaturing gel electrophoresis (CDGE); denaturing gradient gel electrophoresis (DGGE) (Sheffield, V., et al., Proc. Natl. Acad. Sci. USA, 86:232-236 (1989)), mobility shift analysis (Orita, M., et al., Proc. Natl. Acad. Sci. USA, 86:2766-2770 (1989)), restriction enzyme analysis (Flavell, R., et al., Cell, 15:25-41 (1978); Geever, R., et al., Proc. Natl. Acad. Sci. USA, 78:5081-5085 (1981)); heteroduplex analysis; chemical mismatch cleavage (CMC) (Cotton, R., et al., Proc. Natl. Acad. Sci. USA, 85:4397-4401 (1985)); RNase protection assays (Myers, R., et al., Science, 230:1242-1246 (1985); use of polypeptides that recognize nucleotide mismatches, such as E. coli mutS protein; and allele-specific PCR.

In another embodiment of the invention, diagnosis of prostate cancer and/or colorectal cancer or a susceptibility to prostate cancer and/or colorectal cancer can be made by examining expression and/or composition of a polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer in those instances where the genetic marker(s) or haplotype(s) of the present invention result in a change in the composition or expression of the polypeptide. Thus, diagnosis of a susceptibility to prostate cancer and/or colorectal cancer can be made by examining expression and/or composition of one of these polypeptides, or another polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer, in those instances where the genetic marker or haplotype of the present invention results in a change in the composition or expression of the polypeptide. The haplotypes and markers of the present invention that show association to prostate cancer and/or colorectal cancer may play a role through their effect on one or more of these nearby genes. Possible mechanisms affecting these genes include, e.g., effects on transcription, effects on RNA splicing, alterations in relative amounts of alternative splice forms of mRNA, effects on RNA stability, effects on transport from the nucleus to cytoplasm, and effects on the efficiency and accuracy of translation.

Thus, in another embodiment, the variants (markers or haplotypes) of the invention showing association to prostate cancer and/or colorectal cancer affect the expression of a nearby gene. It is well known that regulatory element affecting gene expression may be located far away, even as far as tenths or hundreds of kilobases away, from the promoter region of a gene. By assaying for the presence or absence of at least one allele of at least one polymorphic marker of the present invention, it is thus possible to assess the expression level of such nearby genes.

A variety of methods can be used for detecting protein expression levels, including enzyme linked immunosorbent assays (ELISA), Western blots, immunoprecipitations and immunofluorescence. A test sample from a subject is assessed for the presence of an alteration in the expression and/or an alteration in composition of the polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer. An alteration in expression of a polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer can be, for example, an alteration in the quantitative polypeptide expression (i.e., the amount of polypeptide produced). An alteration in the composition of a polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer is an alteration in the qualitative polypeptide expression (e.g., expression of a mutant polypeptide or of a different splicing variant). In one embodiment, diagnosis of a susceptibility to prostate cancer and/or colorectal cancer is made by detecting a particular splicing variant encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer, or a particular pattern of splicing variants.

Both such alterations (quantitative and qualitative) can also be present. An “alteration” in the polypeptide expression or composition, as used herein, refers to an alteration in expression or composition in a test sample, as compared to the expression or composition of the polypeptide in a control sample. A control sample is a sample that corresponds to the test sample (e.g., is from the same type of cells), and is from a subject who is not affected by, and/or who does not have a susceptibility to, prostate cancer and/or colorectal cancer. In one embodiment, the control sample is from a subject that does not possess a marker allele or haplotype as described herein. Similarly, the presence of one or more different splicing variants in the test sample, or the presence of significantly different amounts of different splicing variants in the test sample, as compared with the control sample, can be indicative of a susceptibility to prostate cancer and/or colorectal cancer. An alteration in the expression or composition of the polypeptide in the test sample, as compared with the control sample, can be indicative of a specific allele in the instance where the allele alters a splice site relative to the reference in the control sample. Various means of examining expression or composition of a polypeptide encoded by a nucleic acid are known to the person skilled in the art and can be used, including spectroscopy, colorimetry, electrophoresis, isoelectric focusing, and immunoassays (e.g., David et al., U.S. Pat. No. 4,376,110) such as immunoblotting (see, e.g., Current Protocols in Molecular Biology, particularly chapter 10, supra).

For example, in one embodiment, an antibody (e.g., an antibody with a detectable label) that is capable of binding to a polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer can be used. Antibodies can be polyclonal or monoclonal. An intact antibody, or a fragment thereof (e.g., Fv, Fab, Fab′, F(ab′)₂) can be used. The term “labeled”, with regard to the probe or antibody, is intended to encompass direct labeling of the probe or antibody by coupling (i.e., physically linking) a detectable substance to the probe or antibody, as well as indirect labeling of the probe or antibody by reactivity with another reagent that is directly labeled. Examples of indirect labeling include detection of a primary antibody using a labeled secondary antibody (e.g., a fluorescently-labeled secondary antibody) and end-labeling of a DNA probe with biotin such that it can be detected with fluorescently-labeled streptavidin.

In one embodiment of this method, the level or amount of polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer in a test sample is compared with the level or amount of the polypeptide in a control sample. A level or amount of the polypeptide in the test sample that is higher or lower than the level or amount of the polypeptide in the control sample, such that the difference is statistically significant, is indicative of an alteration in the expression of the polypeptide encoded by the nucleic acid, and is diagnostic for a particular allele or haplotype responsible for causing the difference in expression. Alternatively, the composition of the polypeptide in a test sample is compared with the composition of the polypeptide in a control sample. In another embodiment, both the level or amount and the composition of the polypeptide can be assessed in the test sample and in the control sample.

In another embodiment, the diagnosis of a susceptibility to prostate cancer and/or colorectal cancer is made by detecting at least one marker or haplotypes of the present invention (e.g., associated alleles of the markers listed in Tables 1-6, and markers in linkage disequilibrium therewith), in combination with an additional protein-based, RNA-based or DNA-based assay. The methods of the invention can also be used in combination with an analysis of a subject's family history and risk factors (e.g., environmental risk factors, lifestyle risk factors).

Kits

Kits useful in the methods of the invention comprise components useful in any of the methods described herein, including for example, primers for nucleic acid amplification, hybridization probes, restriction enzymes (e.g., for RFLP analysis), allele-specific oligonucleotides, antibodies that bind to an altered polypeptide encoded by a nucleic acid of the invention as described herein (e.g., a genomic segment comprising at least one polymorphic marker and/or haplotype of the present invention) or to a non-altered (native) polypeptide encoded by a nucleic acid of the invention as described herein, means for amplification of a nucleic acid associated with prostate cancer and/or colorectal cancer, means for analyzing the nucleic acid sequence of a nucleic acid associated with prostate cancer and/or colorectal cancer, means for analyzing the amino acid sequence of a polypeptide encoded by a nucleic acid associated with prostate cancer and/or colorectal cancer (e.g., a prostate cancer and/or colorectal cancer protein encoded by a prostate cancer and/or colorectal cancer-associated gene), etc. The kits can for example include necessary buffers, nucleic acid primers for amplifying nucleic acids of the invention (e.g., a nucleic acid segment comprising one or more of the polymorphic markers as described herein), and reagents for allele-specific detection of the fragments amplified using such primers and necessary enzymes (e.g., DNA polymerase). Additionally, kits can provide reagents for assays to be used in combination with the methods of the present invention, e.g., reagents for use with other prostate cancer and/or colorectal cancer diagnostic assays.

In one embodiment, the invention is a kit for assaying a sample from a subject to detect the presence of prostate cancer and/or colorectal cancer, symptoms associated with prostate cancer and/or colorectal cancer, or a susceptibility to prostate cancer and/or colorectal cancer in a subject, wherein the kit comprises reagents necessary for selectively detecting at least one allele of at least one polymorphism of the present invention in the genome of the individual. In a particular embodiment, the reagents comprise at least one contiguous oligonucleotide that hybridizes to a fragment of the genome of the individual comprising at least one polymorphism of the present invention. In another embodiment, the reagents comprise at least one pair of oligonucleotides that hybridize to opposite strands of a genomic segment obtained from a subject, wherein each oligonucleotide primer pair is designed to selectively amplify a fragment of the genome of the individual that includes at least one polymorphism, wherein the polymorphism is selected from the group consisting of the polymorphisms as listed in Tables 1-6, and polymorphic markers in linkage disequilibrium therewith. In yet another embodiment the fragment is at least 20 base pairs in size. Such oligonucleotides or nucleic acids (e.g., oligonucleotide primers) can be designed using portions of the nucleic acid sequence flanking polymorphisms (e.g., SNPs or microsatellites) that are indicative of prostate cancer and/or colorectal cancer. In another embodiment, the kit comprises one or more labeled nucleic acids capable of allele-specific detection of one or more specific polymorphic markers or haplotypes associated with prostate cancer and/or colorectal cancer, and reagents for detection of the label. Suitable labels include, e.g., a radioisotope, a fluorescent label, an enzyme label, an enzyme co-factor label, a magnetic label, a spin label, an epitope label.

In particular embodiments, the polymorphic marker or haplotype to be detected by the reagents of the kit comprises one or more markers, two or more markers, three or more markers, four or more markers or five or more markers selected from the group consisting of the markers set forth in Tables 1-6. In another embodiment, the marker or haplotype to be detected comprises the markers set forth in Tables 3 and 4. In another embodiment, the marker or haplotype to be detected comprises at least one marker from the group of markers in strong linkage disequilibrium, as defined by values of r² greater than 0.2, to at least one of the group of markers listed in Tables 3 and 4. In another embodiment, the marker or haplotype to be detected is selected from the group consisting of rs10896450, rs7947353, rs11228565 and rs10943605.

In one preferred embodiment, the kit for detecting the markers of the invention comprises a detection oligonucleotide probe, that hybridizes to a segment of template DNA containing a SNP polymorphisms to be detected, an enhancer oligonucleotide probe and an endonuclease. As explained in the above, the detection oligonucleotide probe comprises a fluorescent moiety or group at its 3′ terminus and a quencher at its 5′ terminus, and an enhancer oligonucleotide, is employed, as described by Kutyavin et al. (Nucleic Acid Res. 34:e128 (2006)). The fluorescent moiety can be Gig Harbor Green or Yakima Yellow, or other suitable fluorescent moieties. The detection probe is designed to hybridize to a short nucleotide sequence that includes the SNP polymorphism to be detected. Preferably, the SNP is anywhere from the terminal residue to −6 residues from the 3′ end of the detection probe. The enhancer is a short oligonucleotide probe which hybridizes to the DNA template 3′ relative to the detection probe. The probes are designed such that a single nucleotide gap exists between the detection probe and the enhancer nucleotide probe when both are bound to the template. The gap creates a synthetic abasic site that is recognized by an endonuclease, such as Endonuclease IV. The enzyme cleaves the dye off the fully complementary detection probe, but cannot cleave a detection probe containing a mismatch. Thus, by measuring the fluorescence of the released fluorescent moiety, assessment of the presence of a particular allele defined by nucleotide sequence of the detection probe can be performed.

The detection probe can be of any suitable size, although preferably the probe is relatively short. In one embodiment, the probe is from 5-100 nucleotides in length. In another embodiment, the probe is from 10-50 nucleotides in length, and in another embodiment, the probe is from 12-30 nucleotides in length. Other lengths of the probe are possible and within scope of the skill of the average person skilled in the art.

In a preferred embodiment, the DNA template containing the SNP polymorphism is amplified by Polymerase Chain Reaction (PCR) prior to detection, and primers for such amplification are included in the reagent kit. In such an embodiment, the amplified DNA serves as the template for the detection probe and the enhancer probe.

Certain embodiments of the detection probe, the enhancer probe, and/or the primers used for amplification of the template by PCR include the use of modified bases, including modified A and modified G. The use of modified bases can be useful for adjusting the melting temperature of the nucleotide molecule (probe and/or primer) to the template DNA, for example for increasing the melting temperature in regions containing a low percentage of G or C bases, in which modified A with the capability of forming three hydrogen bonds to its complementary T can be used, or for decreasing the melting temperature in regions containing a high percentage of G or C bases, for example by using modified G bases that form only two hydrogen bonds to their complementary C base in a double stranded DNA molecule. In a preferred embodiment, modified bases are used in the design of the detection nucleotide probe. Any modified base known to the skilled person can be selected in these methods, and the selection of suitable bases is well within the scope of the skilled person based on the teachings herein and known bases available from commercial sources as known to the skilled person.

In one of such embodiments, determination of the presence of the marker or haplotype is indicative of a susceptibility (increased susceptibility or decreased susceptibility) to prostate cancer and/or colorectal cancer. In another embodiment, the presence of the marker or haplotype is indicative of response to a therapeutic agent for prostate cancer and/or colorectal cancer. In another embodiment, the presence of the marker or haplotype is indicative of prognosis of prostate cancer and/or colorectal cancer. In yet another embodiment, the presence of the marker or haplotype is indicative of progress of treatment of prostate cancer and/or colorectal cancer. Such treatment may include intervention by surgery, medication or by other means (e.g., lifestyle changes).

In a further aspect of the present invention, a pharmaceutical pack (kit) is provided, the pack comprising a therapeutic agent and a set of instructions for administration of the therapeutic agent to humans diagnostically tested for one or more variants of the present invention, as disclosed herein. The therapeutic agent can be a small molecule drug, an antibody, a peptide, an antisense or RNAi molecule, or other therapeutic molecules. In one embodiment, an individual identified as a carrier of at least one variant of the present invention is instructed to take a prescribed dose of the therapeutic agent. In one such embodiment, an individual identified as a homozygous carrier of at least one variant of the present invention is instructed to take a prescribed dose of the therapeutic agent. In another embodiment, an individual identified as a non-carrier of at least one variant of the present invention is instructed to take a prescribed dose of the therapeutic agent.

In certain embodiments, the kit further comprises a set of instructions for using the reagents comprising the kit. In certain embodiments, the kit further comprises a collection of data comprising correlation data between the polymorphic markers assessed by the kit and susceptibility to prostate cancer and/or colorectal cancer.

Therapeutic Agents

Variants of the present invention (e.g., the markers of the invention, e.g., the markers listed in Tables 1-6, e.g., the markers set forth in Tables 3 and 4, and markers in linkage disequilibrium therewith, e.g., rs10896450, rs7947353, rs11228565 and rs10943605) can be used to identify novel therapeutic targets for prostate cancer and/or colorectal cancer. For example, genes containing, or in linkage disequilibrium with, variants (markers and/or haplotypes) associated with prostate cancer and/or colorectal cancer, or their products, as well as genes or their products that are directly or indirectly regulated by or interact with these variant genes or their products, can be targeted for the development of therapeutic agents to treat prostate cancer and/or colorectal cancer, or prevent or delay onset of symptoms associated with prostate cancer and/or colorectal cancer. Therapeutic agents may comprise one or more of, for example, small non-protein and non-nucleic acid molecules, proteins, peptides, protein fragments, nucleic acids (DNA, RNA), PNA (peptide nucleic acids), or their derivatives or mimetics which can modulate the function and/or levels of the target genes or their gene products.

The nucleic acids and/or variants of the invention, or nucleic acids comprising their complementary sequence, may be used as antisense constructs to control gene expression in cells, tissues or organs. The methodology associated with antisense techniques is well known to the skilled artisan, and is described and reviewed in AntisenseDrug Technology: Principles, Strategies, and Applications, Crooke, ed., Marcel Dekker Inc., New York (2001). In general, antisense agents (antisense oligonucleotides) are comprised of single stranded oligonucleotides (RNA or DNA) that are capable of binding to a complimentary nucleotide segment. By binding the appropriate target sequence, an RNA-RNA, DNA-DNA or RNA-DNA duplex is formed. The antisense oligonucleotides are complementary to the sense or coding strand of a gene. It is also possible to form a triple helix, where the antisense oligonucleotide binds to duplex DNA.

Several classes of antisense oligonucleotide are known to those skilled in the art, including cleavers and blockers. The former bind to target RNA sites, activate intracellular nucleases (e.g., RnaseH or Rnase L), that cleave the target RNA. Blockers bind to target RNA, inhibit protein translation by steric hindrance of the ribosomes. Examples of blockers include nucleic acids, morpholino compounds, locked nucleic acids and methylphosphonates (Thompson, Drug Discovery Today, 7:912-917 (2002)). Antisense oligonucleotides are useful directly as therapeutic agents, and are also useful for determining and validating gene function, for example by gene knock-out or gene knock-down experiments. Antisense technology is further described in Layery et al., Curr. Opin. Drug Discov. Devel. 6:561-569 (2003), Stephens et al., Curr. Opin. Mol. Ther. 5:118-122 (2003), Kurreck, Eur. J. Biochem. 270:1628-44 (2003), Dias et al., Mol. Cancer Ter. 1:347-55 (2002), Chen, Methods Mol. Med. 75:621-636 (2003), Wang et al., Curr. Cancer Drug Targets 1:177-96 (2001), and Bennett, Antisense Nucleic Acid Drug. Dev. 12:215-24 (2002).

In certain embodiments, the antisense agent is an oligonucleotide that is capable of binding to a nucleotide segment of the LD Block C11 or LD Block C06, as described herein. Antisense nucleotides can be from 5-500 nucleotides in length, including 5-200 nucleotides, 5-100 nucleotides, 8-50 nucleotides, and 8-30 nucleotides. In certain preferred embodiments, the antisense nucleotides is from 14-50 nucleotides in length, including 14-40 nucleotides and 14-30 nucleotides. In certain such embodiments, the antisense nucleotide is capable of binding to a nucleotide segment of LD Block C11 as set forth in SEQ ID NO:201.

The variants described herein can be used for the selection and design of antisense reagents that are specific for particular variants. Using information about the variants described herein, antisense oligonucleotides or other antisense molecules that specifically target mRNA molecules that contain one or more variants of the invention can be designed. In this manner, expression of mRNA molecules that contain one or more variant of the present invention (markers and/or haplotypes) can be inhibited or blocked. In one embodiment, the antisense molecules are designed to specifically bind a particular allelic form (i.e., one or several variants (alleles and/or haplotypes)) of the target nucleic acid, thereby inhibiting translation of a product originating from this specific allele or haplotype, but which do not bind other or alternate variants at the specific polymorphic sites of the target nucleic acid molecule.

As antisense molecules can be used to inactivate mRNA so as to inhibit gene expression, and thus protein expression, the molecules can be used to treat a disease or disorder, including prostate cancer and/or colorectal cancer. The methodology can involve cleavage by means of ribozymes containing nucleotide sequences complementary to one or more regions in the mRNA that attenuate the ability of the mRNA to be translated. Such mRNA regions include, for example, protein-coding regions, in particular protein-coding regions corresponding to catalytic activity, substrate and/or ligand binding sites, or other functional domains of a protein.

The phenomenon of RNA interference (RNAi) has been actively studied for the last decade, since its original discovery in C. elegans (Fire et al., Nature 391:806-11 (1998)), and in recent years its potential use in treatment of human disease has been actively pursued (reviewed in Kim & Rossi, Nature Rev. Genet. 8:173-204 (2007)). RNA interference (RNAi), also called gene silencing, is based on using double-stranded RNA molecules (dsRNA) to turn off specific genes. In the cell, cytoplasmic double-stranded RNA molecules (dsRNA) are processed by cellular complexes into small interfering RNA (siRNA). The siRNA guide the targeting of a protein-RNA complex to specific sites on a target mRNA, leading to cleavage of the mRNA (Thompson, Drug Discovery Today, 7:912-917 (2002)). The siRNA molecules are typically about 20, 21, 22 or 23 nucleotides in length. Thus, one aspect of the invention relates to isolated nucleic acid molecules, and the use of those molecules for RNA interference, i.e. as small interfering RNA molecules (siRNA). In one embodiment, the isolated nucleic acid molecules are 18-26 nucleotides in length, preferably 19-25 nucleotides in length, more preferably 20-24 nucleotides in length, and more preferably 21, 22 or 23 nucleotides in length.

Another pathway for RNAi-mediated gene silencing originates in endogenously encoded primary microRNA (pri-miRNA) transcripts, which are processed in the cell to generate precursor miRNA (pre-miRNA). These miRNA molecules are exported from the nucleus to the cytoplasm, where they undergo processing to generate mature miRNA molecules (miRNA), which direct translational inhibition by recognizing target sites in the 3′ untranslated regions of mRNAs, and subsequent mRNA degradation by processing P-bodies (reviewed in Kim & Rossi, Nature Rev. Genet. 8:173-204 (2007)).

Clinical applications of RNAi include the incorporation of synthetic siRNA duplexes, which preferably are approximately 20-23 nucleotides in size, and preferably have 3′ overlaps of 2 nucleotides. Knockdown of gene expression is established by sequence-specific design for the target mRNA. Several commercial sites for optimal design and synthesis of such molecules are known to those skilled in the art.

Other applications provide longer siRNA molecules (typically 25-30 nucleotides in length, preferably about 27 nucleotides), as well as small hairpin RNAs (shRNAs; typically about 29 nucleotides in length). The latter are naturally expressed, as described in Amarzguioui et al. (FEBS Lett. 579:5974-81 (2005)). Chemically synthetic siRNAs and shRNAs are substrates for in vivo processing, and in some cases provide more potent gene-silencing than shorter designs (Kim et al., Nature Biotechnol. 23:222-226 (2005); Siolas et al., Nature Biotechnol. 23:227-231 (2005)). In general siRNAs provide for transient silencing of gene expression, because their intracellular concentration is diluted by subsequent cell divisions. By contrast, expressed shRNAs mediate long-term, stable knockdown of target transcripts, for as long as transcription of the shRNA takes place (Marques et al., Nature Biotechnol. 23:559-565 (2006); Brummelkamp et al., Science 296: 550-553 (2002)).

Since RNAi molecules, including siRNA, miRNA and shRNA, act in a sequence-dependent manner, the variants of the present invention (e.g., the markers set forth in Tables 1-6, e.g., the markers set forth in Tables 3 and 4) can be used to design RNAi reagents that recognize specific nucleic acid molecules comprising specific alleles and/or haplotypes (e.g., the alleles and/or haplotypes of the present invention), while not recognizing nucleic acid molecules comprising other alleles or haplotypes. These RNAi reagents can thus recognize and destroy the target nucleic acid molecules. As with antisense reagents, RNAi reagents can be useful as therapeutic agents (i.e., for turning off disease-associated genes or disease-associated gene variants), but may also be useful for characterizing and validating gene function (e.g., by gene knock-out or gene knock-down experiments).

Delivery of RNAi may be performed by a range of methodologies known to those skilled in the art. Methods utilizing non-viral delivery include cholesterol, stable nucleic acid-lipid particle (SNALP), heavy-chain antibody fragment (Fab), aptamers and nanoparticles. Viral delivery methods include use of lentivirus, adenovirus and adeno-associated virus. The siRNA molecules are in some embodiments chemically modified to increase their stability. This can include modifications at the 2′ position of the ribose, including 2′-O-methylpurines and 2′-fluoropyrimidines, which provide resistance to Rnase activity. Other chemical modifications are possible and known to those skilled in the art.

The following references provide a further summary of RNAi, and possibilities for targeting specific genes using RNAi: Kim & Rossi, Nat. Rev. Genet. 8:173-184 (2007), Chen & Rajewsky, Nat. Rev. Genet. 8: 93-103 (2007), Reynolds, et al., Nat. Biotechnol. 22:326-330 (2004), Chi et al., Proc. Natl. Acad. Sci. USA 100:6343-6346 (2003), Vickers et al., J. Biol. Chem. 278:7108-7118 (2003), Agami, Curr. Opin. Chem. Biol. 6:829-834 (2002), Layery, et al., Curr. Opin. Drug Discov. Devel. 6:561-569 (2003), Shi, Trends Genet. 19:9-12 (2003), Shuey et al., Drug Discov. Today 7:1040-46 (2002), McManus et al., Nat. Rev. Genet. 3:737-747 (2002), Xia et al., Nat. Biotechnol. 20:1006-10 (2002), Plasterk et al., curr. Opin. Genet. Dev. 10:562-7 (2000), Bosher et al., Nat. Cell Biol. 2:E31-6 (2000), and Hunter, Curr. Biol. 9:R440-442 (1999).

A genetic defect leading to increased predisposition or risk for development of a disease, such as prostate cancer and/or colorectal cancer, or a defect causing the disease, may be corrected permanently by administering to a subject carrying the defect a nucleic acid fragment that incorporates a repair sequence that supplies the normal/wild-type nucleotide(s) at the site of the genetic defect. Such site-specific repair sequence may concompass an RNA/DNA oligonucleotide that operates to promote endogenous repair of a subject's genomic DNA. The administration of the repair sequence may be performed by an appropriate vehicle, such as a complex with polyethelenimine, encapsulated in anionic liposomes, a viral vector such as an adenovirus vector, or other pharmaceutical compositions suitable for promoting intracellular uptake of the administered nucleic acid. The genetic defect may then be overcome, since the chimeric oligonucleotides induce the incorporation of the normal sequence into the genome of the subject, leading to expression of the normal/wild-type gene product. The replacement is propagated, thus rendering a permanent repair and alleviation of the symptoms associated with the disease or condition.

The present invention provides methods for identifying compounds or agents that can be used to treat prostate cancer and/or colorectal cancer. Thus, the variants of the invention are useful as targets for the identification and/or development of therapeutic agents. Such methods may include assaying the ability of an agent or compound to modulate the activity and/or expression of a nucleic acid that includes at least one of the variants (markers and/or haplotypes) of the present invention, or the encoded product of the nucleic acid. This in turn can be used to identify agents or compounds that inhibit or alter the undesired activity or expression of the encoded nucleic acid product. Assays for performing such experiments can be performed in cell-based systems or in cell-free systems, as known to the skilled person. Cell-based systems include cells naturally expressing the nucleic acid molecules of interest, or recombinant cells that have been genetically modified so as to express a certain desired nucleic acid molecule.

Variant gene expression in a patient can be assessed by expression of a variant-containing nucleic acid sequence (for example, a gene containing at least one variant of the present invention, which can be transcribed into RNA containing the at least one variant, and in turn translated into protein), or by altered expression of a normal/wild-type nucleic acid sequence due to variants affecting the level or pattern of expression of the normal transcripts, for example variants in the regulatory or control region of the gene. Assays for gene expression include direct nucleic acid assays (mRNA), assays for expressed protein levels, or assays of collateral compounds involved in a pathway, for example a signal pathway. Furthermore, the expression of genes that are up- or down-regulated in response to the signal pathway can also be assayed. One embodiment includes operably linking a reporter gene, such as luciferase, to the regulatory region of the gene(s) of interest.

Modulators of gene expression can in one embodiment be identified when a cell is contacted with a candidate compound or agent, and the expression of mRNA is determined. The expression level of mRNA in the presence of the candidate compound or agent is compared to the expression level in the absence of the compound or agent. Based on this comparison, candidate compounds or agents for treating prostate cancer and/or colorectal cancer can be identified as those modulating the gene expression of the variant gene. When expression of mRNA or the encoded protein is statistically significantly greater in the presence of the candidate compound or agent than in its absence, then the candidate compound or agent is identified as a stimulator or up-regulator of expression of the nucleic acid. When nucleic acid expression or protein level is statistically significantly less in the presence of the candidate compound or agent than in its absence, then the candidate compound is identified as an inhibitor or down-regulator of the nucleic acid expression.

The invention further provides methods of treatment using a compound identified through drug (compound and/or agent) screening as a gene modulator (i.e. stimulator and/or inhibitor of gene expression).

Methods of Assessing Probability of Response to Therapeutic Agents, Methods of Monitoring Progress of Treatment and Methods of Treatment

As is known in the art, individuals can have differential responses to a particular therapy (e.g., a therapeutic agent or therapeutic method). Pharmacogenomics addresses the issue of how genetic variations (e.g., the variants (markers and/or haplotypes) of the present invention) affect drug response, due to altered drug disposition and/or abnormal or altered action of the drug. Thus, the basis of the differential response may be genetically determined in part. Clinical outcomes due to genetic variations affecting drug response may result in toxicity of the drug in certain individuals (e.g., carriers or non-carriers of the genetic variants of the present invention), or therapeutic failure of the drug. Therefore, the variants of the present invention may determine the manner in which a therapeutic agent and/or method acts on the body, or the way in which the body metabolizes the therapeutic agent.

Accordingly, in one embodiment, the presence of a particular allele at a polymorphic site or haplotype is indicative of a different, e.g. a different response rate, to a particular treatment modality for prostate cancer and/or colorectal cancer. This means that a patient diagnosed with prostate cancer and/or colorectal cancer, and carrying a certain allele at a polymorphic or haplotype of the present invention (e.g., the at-risk and protective alleles and/or haplotypes of the invention) would respond better to, or worse to, a specific therapeutic, drug therapy and/or other therapy used to treat the disease. Therefore, the presence or absence of the marker allele or haplotype could aid in deciding what treatment should be used for a the patient. For example, for a newly diagnosed patient, the presence of a marker or haplotype of the present invention may be assessed (e.g., through testing DNA derived from a blood sample, as described herein). If the patient is positive for a marker allele or haplotype at (that is, at least one specific allele of the marker, or haplotype, is present), then the physician recommends one particular therapy, while if the patient is negative for the at least one allele of a marker, or a haplotype, then a different course of therapy may be recommended (which may include recommending that no immediate therapy, other than serial monitoring for progression of the disease, be performed). Thus, the patient's carrier status could be used to help determine whether a particular treatment modality should be administered. The value lies within the possibilities of being able to diagnose the disease at an early stage, to select the most appropriate treatment, and provide information to the clinician about prognosis/aggressiveness of the disease in order to be able to apply the most appropriate treatment.

The present invention also relates to methods of monitoring progress or effectiveness of a treatment for a prostate cancer and/or colorectal cancer. This can be done based on the genotype and/or haplotype status of the markers and haplotypes of the present invention, i.e., by assessing the absence or presence of at least one allele of at least one polymorphic marker as disclosed herein, or by monitoring expression of genes that are associated with the variants (markers and haplotypes) of the present invention. The risk gene mRNA or the encoded polypeptide can be measured in a tissue sample (e.g., a peripheral blood sample, or a biopsy sample). Expression levels and/or mRNA levels can thus be determined before and during treatment to monitor its effectiveness. Alternatively, or concomitantly, the genotype and/or haplotype status of at least one risk variant for prostate cancer and/or colorectal cancer as presented herein is determined before and during treatment to monitor its effectiveness.

Alternatively, biological networks or metabolic pathways related to the markers and haplotypes of the present invention can be monitored by determining mRNA and/or polypeptide levels. This can be done for example, by monitoring expression levels or polypeptides for several genes belonging to the network and/or pathway, in samples taken before and during treatment. Alternatively, metabolites belonging to the biological network or metabolic pathway can be determined before and during treatment. Effectiveness of the treatment is determined by comparing observed changes in expression levels/metabolite levels during treatment to corresponding data from healthy subjects.

In a further aspect, the markers of the present invention can be used to increase power and effectiveness of clinical trials. Thus, individuals who are carriers of at least one at-risk variant of the present invention, i.e. individuals who are carriers of at least one allele of at least one polymorphic marker conferring increased risk of developing prostate cancer and/or colorectal cancer may be more likely to respond to a particular treatment modality. In one embodiment, individuals who carry at-risk variants for gene(s) in a pathway and/or metabolic network for which a particular treatment (e.g., small molecule drug) is targeting, are more likely to be responders to the treatment. In another embodiment, individuals who carry at-risk variants for a gene, which expression and/or function is altered by the at-risk variant, are more likely to be responders to a treatment modality targeting that gene, its expression or its gene product. This application can improve the safety of clinical trials, but can also enhance the chance that a clinical trial will demonstrate statistically significant efficacy, which may be limited to a certain sub-group of the population. Thus, one possible outcome of such a trial is that carriers of certain genetic variants, e.g., the markers and haplotypes of the present invention, are statistically significantly likely to show positive response to the therapeutic agent, i.e. experience alleviation of symptoms associated with prostate cancer and/or colorectal cancer when taking the therapeutic agent or drug as prescribed.

In a further aspect, the markers and haplotypes of the present invention can be used for targeting the selection of pharmaceutical agents for specific individuals. Personalized selection of treatment modalities, lifestyle changes or combination of lifestyle changes and administration of particular treatment, can be realized by the utilization of the at-risk variants of the present invention. Thus, the knowledge of an individual's status for particular markers of the present invention, can be useful for selection of treatment options that target genes or gene products affected by the at-risk variants of the invention. Certain combinations of variants may be suitable for one selection of treatment options, while other gene variant combinations may target other treatment options. Such combination of variant may include one variant, two variants, three variants, or four or more variants, as needed to determine with clinically reliable accuracy the selection of treatment module.

Computer-Implemented Aspects

As understood by those of ordinary skill in the art, the methods and information described herein may be implemented, in all or in part, as computer executable instructions on known computer readable media. For example, the methods described herein may be implemented in hardware. Alternatively, the method may be implemented in software stored in, for example, one or more memories or other computer readable medium and implemented on one or more processors. As is known, the processors may be associated with one or more controllers, calculation units and/or other units of a computer system, or implanted in firmware as desired. If implemented in software, the routines may be stored in any computer readable memory such as in RAM, ROM, flash memory, a magnetic disk, a laser disk, or other storage medium, as is also known. Likewise, this software may be delivered to a computing device via any known delivery method including, for example, over a communication channel such as a telephone line, the Internet, a wireless connection, etc., or via a transportable medium, such as a computer readable disk, flash drive, etc.

More generally, and as understood by those of ordinary skill in the art, the various steps described above may be implemented as various blocks, operations, tools, modules and techniques which, in turn, may be implemented in hardware, firmware, software, or any combination of hardware, firmware, and/or software. When implemented in hardware, some or all of the blocks, operations, techniques, etc. may be implemented in, for example, a custom integrated circuit (IC), an application specific integrated circuit (ASIC), a field programmable logic array (FPGA), a programmable logic array (PLA), etc.

When implemented in software, the software may be stored in any known computer readable medium such as on a magnetic disk, an optical disk, or other storage medium, in a RAM or ROM or flash memory of a computer, processor, hard disk drive, optical disk drive, tape drive, etc. Likewise, the software may be delivered to a user or a computing system via any known delivery method including, for example, on a computer readable disk or other transportable computer storage mechanism.

The FIGURE illustrates an example of a suitable computing system environment 100 on which a system for the steps of the claimed method and apparatus may be implemented. The computing system environment 100 is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the method or apparatus of the claims. Neither should the computing environment 100 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment 100.

The steps of the claimed method and system are operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that may be suitable for use with the methods or system of the claims include, but are not limited to, personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices; and the like.

The steps of the claimed method and system may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The methods and apparatus may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In both integrated and distributed computing environments, program modules may be located in both local and remote computer storage media including memory storage devices.

With reference to the FIGURE, an exemplary system for implementing the steps of the claimed method and system includes a general purpose computing device in the form of a computer 110. Components of computer 110 may include, but are not limited to, a processing unit 120, a system memory 130, and a system bus 121 that couples various system components including the system memory to the processing unit 120. The system bus 121 may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (USA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus also known as Mezzanine bus.

Computer 110 typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 110 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by computer 110. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of the any of the above should also be included within the scope of computer readable media.

The system memory 130 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 131 and random access memory (RAM) 132. A basic input/output system 133 (BIOS), containing the basic routines that help to transfer information between elements within computer 110, such as during start-up, is typically stored in ROM 131. RAM 132 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 120. By way of example, and not limitation, the FIGURE illustrates operating system 134, application programs 135, other program modules 136, and program data 137.

The computer 110 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only, the FIGURE illustrates a hard disk drive 140 that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive 151 that reads from or writes to a removable, nonvolatile magnetic disk 152, and an optical disk drive 155 that reads from or writes to a removable, nonvolatile optical disk 156 such as a CD ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The hard disk drive 141 is typically connected to the system bus 121 through a non-removable memory interface such as interface 140, and magnetic disk drive 151 and optical disk drive 155 are typically connected to the system bus 121 by a removable memory interface, such as interface 150.

The drives and their associated computer storage media discussed above and illustrated in the FIGURE, provide storage of computer readable instructions, data structures, program modules and other data for the computer 110. In the FIGURE, for example, hard disk drive 141 is illustrated as storing operating system 144, application programs 145, other program modules 146, and program data 147. Note that these components can either be the same as or different from operating system 134, application programs 135, other program modules 136, and program data 137. Operating system 144, application programs 145, other program modules 146, and program data 147 are given different numbers here to illustrate that, at a minimum, they are different copies. A user may enter commands and information into the computer 20 through input devices such as a keyboard 162 and pointing device 161, commonly referred to as a mouse, trackball or touch pad. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit 120 through a user input interface 160 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB). A monitor 191 or other type of display device is also connected to the system bus 121 via an interface, such as a video interface 190. In addition to the monitor, computers may also include other peripheral output devices such as speakers 197 and printer 196, which may be connected through an output peripheral interface 190.

The computer 110 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 180. The remote computer 180 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 110, although only a memory storage device 181 has been illustrated in the FIGURE. The logical connections depicted in FIGURE include a local area network (LAN) 171 and a wide area network (WAN) 173, but may also include other networks. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet.

When used in a LAN networking environment, the computer 110 is connected to the LAN 171 through a network interface or adapter 170. When used in a WAN networking environment, the computer 110 typically includes a modem 172 or other means for establishing communications over the WAN 173, such as the Internet. The modem 172, which may be internal or external, may be connected to the system bus 121 via the user input interface 160, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 110, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation, the FIGURE illustrates remote application programs 185 as residing on memory device 181. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.

Although the forgoing text sets forth a detailed description of numerous different embodiments of the invention, it should be understood that the scope of the invention is defined by the words of the claims set forth at the end of this patent. The detailed description is to be construed as exemplary only and does not describe every possibly embodiment of the invention because describing every possible embodiment would be impractical, if not impossible. Numerous alternative embodiments could be implemented, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims defining the invention.

While the risk evaluation system and method, and other elements, have been described as preferably being implemented in software, they may be implemented in hardware, firmware, etc., and may be implemented by any other processor. Thus, the elements described herein may be implemented in a standard multi-purpose CPU or on specifically designed hardware or firmware such as an application-specific integrated circuit (ASIC) or other hard-wired device as desired, including, but not limited to, the computer 110 of the FIGURE. When implemented in software, the software routine may be stored in any computer readable memory such as on a magnetic disk, a laser disk, or other storage medium, in a RAM or ROM of a computer or processor, in any database, etc. Likewise, this software may be delivered to a user or a diagnostic system via any known or desired delivery method including, for example, on a computer readable disk or other transportable computer storage mechanism or over a communication channel such as a telephone line, the interne, wireless communication, etc. (which are viewed as being the same as or interchangeable with providing such software via a transportable storage medium).

Thus, many modifications and variations may be made in the techniques and structures described and illustrated herein without departing from the spirit and scope of the present invention. Thus, it should be understood that the methods and apparatus described herein are illustrative only and are not limiting upon the scope of the invention.

Accordingly, the invention relates to computer-implemented applications using the polymorphic markers and haplotypes described herein, and genotype and/or disease-association data derived therefrom. Such applications can be useful for storing, manipulating or otherwise analyzing genotype data that is useful in the methods of the invention. One example pertains to storing genotype information derived from an individual on readable media, so as to be able to provide the genotype information to a third party (e.g., the individual, a guardian of the individual, a health care provider or genetic analysis service provider), or for deriving information from the genotype data, e.g., by comparing the genotype data to information about genetic risk factors contributing to increased susceptibility to prostate and/or colorectal cancer, and reporting results based on such comparison.

In general terms, computer-readable media has capabilities of storing (i) identifier information for at least one polymorphic marker or a haplotype, as described herein; (ii) an indicator of the frequency of at least one allele of said at least one marker, or the frequency of a haplotype, in individuals with prostate cancer and/or colorectal cancer; and an indicator of the frequency of at least one allele of said at least one marker, or the frequency of a haplotype, in a reference population. The reference population can be a disease-free population of individuals. Alternatively, the reference population is a random sample from the general population, and is thus representative of the population at large. The frequency indicator may be a calculated frequency, a count of alleles and/or haplotype copies, or normalized or otherwise manipulated values of the actual frequencies that are suitable for the particular medium.

The markers and haplotypes described herein to be associated with increased susceptibility (e.g., increased risk) of prostate and colorectal cancer, are in certain embodiments useful for interpretation and/or analysis of genotype data. Thus in certain embodiments, an identification of an at-risk allele for prostate cancer and/or colorectal cancer, as shown herein, or an allele at a polymorphic marker in LD with any one of the markers shown herein to be associated with these cancers, is indicative of the individual from whom the genotype data originates is at increased risk of prostate cancer and/or colorectal cancer. In one such embodiment, genotype data is generated for at least one such polymorphic marker, or a marker in linkage disequilibrium therewith. The genotype data is subsequently made available to a third party, such as the individual from whom the data originates, his/her guardian or representative, a physician or health care worker, genetic counselor, or insurance agent, for example via a user interface accessible over the internet, together with an interpretation of the genotype data, e.g., in the form of a risk measure (such as an absolute risk (AR), risk ratio (RR) or odds ratio (OR)) for the disease. In another embodiment, at-risk markers identified in a genotype dataset derived from an individual are assessed and results from the assessment of the risk conferred by the presence of such at-risk variants in the dataset are made available to the third party, for example via a secure web interface, or by other communication means. The results of such risk assessment can be reported in numeric form (e.g., by risk values, such as absolute risk, relative risk, and/or an odds ratio, or by a percentage increase in risk compared with a reference), by graphical means, or by other means suitable to illustrate the risk to the individual from whom the genotype data is derived.

Nucleic Acids and Polypeptides

The nucleic acids and polypeptides described herein can be used in methods an kits of the present invention, as described in the above.

An “isolated” nucleic acid molecule, as used herein, is one that is separated from nucleic acids that normally flank the gene or nucleotide sequence (as in genomic sequences) and/or has been completely or partially purified from other transcribed sequences (e.g., as in an RNA library). For example, an isolated nucleic acid of the invention can be substantially isolated with respect to the complex cellular milieu in which it naturally occurs, or culture medium when produced by recombinant techniques, or chemical precursors or other chemicals when chemically synthesized. In some instances, the isolated material will form part of a composition (for example, a crude extract containing other substances), buffer system or reagent mix. In other circumstances, the material can be purified to essential homogeneity, for example as determined by polyacrylamide gel electrophoresis (PAGE) or column chromatography (e.g., HPLC). An isolated nucleic acid molecule of the invention can comprise at least about 50%, at least about 80% or at least about 90% (on a molar basis) of all macromolecular species present. With regard to genomic DNA, the term “isolated” also can refer to nucleic acid molecules that are separated from the chromosome with which the genomic DNA is naturally associated. For example, the isolated nucleic acid molecule can contain less than about 250 kb, 200 kb, 150 kb, 100 kb, 75 kb, 50 kb, 25 kb, 10 kb, 5 kb, 4 kb, 3 kb, 2 kb, 1 kb, 0.5 kb or 0.1 kb of the nucleotides that flank the nucleic acid molecule in the genomic DNA of the cell from which the nucleic acid molecule is derived.

The nucleic acid molecule can be fused to other coding or regulatory sequences and still be considered isolated. Thus, recombinant DNA contained in a vector is included in the definition of “isolated” as used herein. Also, isolated nucleic acid molecules include recombinant DNA molecules in heterologous host cells or heterologous organisms, as well as partially or substantially purified DNA molecules in solution. “Isolated” nucleic acid molecules also encompass in vivo and in vitro RNA transcripts of the DNA molecules of the present invention. An isolated nucleic acid molecule or nucleotide sequence can include a nucleic acid molecule or nucleotide sequence that is synthesized chemically or by recombinant means. Such isolated nucleotide sequences are useful, for example, in the manufacture of the encoded polypeptide, as probes for isolating homologous sequences (e.g., from other mammalian species), for gene mapping (e.g., by in situ hybridization with chromosomes), or for detecting expression of the gene in tissue (e.g., human tissue), such as by Northern blot analysis or other hybridization techniques.

The invention also pertains to nucleic acid molecules that hybridize under high stringency hybridization conditions, such as for selective hybridization, to a nucleotide sequence described herein (e.g., nucleic acid molecules that specifically hybridize to a nucleotide sequence containing a polymorphic site associated with a marker or haplotype described herein). Such nucleic acid molecules can be detected and/or isolated by allele- or sequence-specific hybridization (e.g., under high stringency conditions). Stringency conditions and methods for nucleic acid hybridizations are well known to the skilled person (see, e.g., Current Protocols in Molecular Biology, Ausubel, F. et al, John Wiley & Sons, (1998), and Kraus, M. and Aaronson, S., Methods Enzymol., 200:546-556 (1991), the entire teachings of which are incorporated by reference herein.

The percent identity of two nucleotide or amino acid sequences can be determined by aligning the sequences for optimal comparison purposes (e.g., gaps can be introduced in the sequence of a first sequence). The nucleotides or amino acids at corresponding positions are then compared, and the percent identity between the two sequences is a function of the number of identical positions shared by the sequences (i.e., % identity=# of identical positions/total # of positions×100). In certain embodiments, the length of a sequence aligned for comparison purposes is at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95%, of the length of the reference sequence. The actual comparison of the two sequences can be accomplished by well-known methods, for example, using a mathematical algorithm. A non-limiting example of such a mathematical algorithm is described in Karlin, S, and Altschul, S., Proc. Natl. Acad. Sci. USA, 90:5873-5877 (1993). Such an algorithm is incorporated into the NBLAST and XBLAST programs (version 2.0), as described in Altschul, S. et al., Nucleic Acids Res., 25:3389-3402 (1997). When utilizing BLAST and Gapped BLAST programs, the default parameters of the respective programs (e.g., NBLAST) can be used. See the website on the world wide web at ncbi.nlm.nih.gov. In one embodiment, parameters for sequence comparison can be set at score=100, wordlength=12, or can be varied (e.g., W=5 or W=20).

Other examples include the algorithm of Myers and Miller, CABIOS (1989), ADVANCE and ADAM as described in Torellis, A. and Robotti, C., Comput. Appl. Biosci. 10:3-5 (1994); and FASTA described in Pearson, W. and Lipman, D., Proc. Natl. Acad. Sci. USA, 85:2444-48 (1988). In another embodiment, the percent identity between two amino acid sequences can be accomplished using the GAP program in the GCG software package (Accelrys, Cambridge, UK).

The present invention also provides isolated nucleic acid molecules that contain a fragment or portion that hybridizes under highly stringent conditions to a nucleic acid that comprises, or consists of, the nucleotide sequence of LD Block C06 and/or LD Block C11, as defined herein, or a nucleotide sequence comprising, or consisting of, the complement of the nucleotide sequence of LD Block C06 and/or LD Block C11, wherein the nucleotide sequence comprises at least one polymorphic allele contained in the markers and haplotypes described herein. The nucleic acid fragments of the invention are at least about 15, at least about 18, 20, 23 or 25 nucleotides, and can be 30, 40, 50, 100, 200, 500, 1000, 10,000 or more nucleotides in length.

The nucleic acid fragments of the invention are used as probes or primers in assays such as those described herein. “Probes” or “primers” are oligonucleotides that hybridize in a base-specific manner to a complementary strand of a nucleic acid molecule. In addition to DNA and RNA, such probes and primers include polypeptide nucleic acids (PNA), as described in Nielsen, P. et al., Science 254:1497-1500 (1991). A probe or primer comprises a region of nucleotide sequence that hybridizes to at least about 15, typically about 20-25, and in certain embodiments about 40, 50 or 75, consecutive nucleotides of a nucleic acid molecule. In one embodiment, the probe or primer comprises at least one allele of at least one polymorphic marker or at least one haplotype described herein, or the complement thereof. In particular embodiments, a probe or primer can comprise 100 or fewer nucleotides; for example, in certain embodiments from 6 to 50 nucleotides, or, for example, from 12 to 30 nucleotides. In other embodiments, the probe or primer is at least 70% identical, at least 80% identical, at least 85% identical, at least 90% identical, or at least 95% identical, to the contiguous nucleotide sequence or to the complement of the contiguous nucleotide sequence. In another embodiment, the probe or primer is capable of selectively hybridizing to the contiguous nucleotide sequence or to the complement of the contiguous nucleotide sequence. Often, the probe or primer further comprises a label, e.g., a radioisotope, a fluorescent label, an enzyme label, an enzyme co-factor label, a magnetic label, a spin label, an epitope label.

The nucleic acid molecules of the invention, such as those described above, can be identified and isolated using standard molecular biology techniques well known to the skilled person. The amplified DNA can be labeled (e.g., radiolabeled) and used as a probe for screening a cDNA library derived from human cells. The cDNA can be derived from mRNA and contained in a suitable vector. Corresponding clones can be isolated, DNA can obtained following in vivo excision, and the cloned insert can be sequenced in either or both orientations by art-recognized methods to identify the correct reading frame encoding a polypeptide of the appropriate molecular weight. Using these or similar methods, the polypeptide and the DNA encoding the polypeptide can be isolated, sequenced and further characterized.

Antibodies

The invention also provides antibodies which bind to an epitope comprising either a variant amino acid sequence (e.g., comprising an amino acid substitution) encoded by a variant allele or the reference amino acid sequence encoded by the corresponding non-variant or wild-type allele. The term “antibody” as used herein refers to immunoglobulin molecules and immunologically active portions of immunoglobulin molecules, i.e., molecules that contain antigen-binding sites that specifically bind an antigen. A molecule that specifically binds to a polypeptide of the invention is a molecule that binds to that polypeptide or a fragment thereof, but does not substantially bind other molecules in a sample, e.g., a biological sample, which naturally contains the polypeptide. Examples of immunologically active portions of immunoglobulin molecules include F(ab) and F(ab′)₂ fragments which can be generated by treating the antibody with an enzyme such as pepsin. The invention provides polyclonal and monoclonal antibodies that bind to a polypeptide of the invention. The term “monoclonal antibody” or “monoclonal antibody composition”, as used herein, refers to a population of antibody molecules that contain only one species of an antigen binding site capable of immunoreacting with a particular epitope of a polypeptide of the invention. A monoclonal antibody composition thus typically displays a single binding affinity for a particular polypeptide of the invention with which it immunoreacts.

Polyclonal antibodies can be prepared as described above by immunizing a suitable subject with a desired immunogen, e.g., polypeptide of the invention or a fragment thereof. The antibody titer in the immunized subject can be monitored over time by standard techniques, such as with an enzyme linked immunosorbent assay (ELISA) using immobilized polypeptide. If desired, the antibody molecules directed against the polypeptide can be isolated from the mammal (e.g., from the blood) and further purified by well-known techniques, such as protein A chromatography to obtain the IgG fraction. At an appropriate time after immunization, e.g., when the antibody titers are highest, antibody-producing cells can be obtained from the subject and used to prepare monoclonal antibodies by standard techniques, such as the hybridoma technique originally described by Kohler and Milstein, Nature 256:495-497 (1975), the human B cell hybridoma technique (Kozbor et al., Immunol. Today 4: 72 (1983)), the EBV-hybridoma technique (Cole et al., Monoclonal Antibodies and Cancer Therapy, Alan R. Liss, 1985, Inc., pp. 77-96) or trioma techniques. The technology for producing hybridomas is well known (see generally Current Protocols in Immunology (1994) Coligan et al., (eds.) John Wiley & Sons, Inc., New York, N.Y.). Briefly, an immortal cell line (typically a myeloma) is fused to lymphocytes (typically splenocytes) from a mammal immunized with an immunogen as described above, and the culture supernatants of the resulting hybridoma cells are screened to identify a hybridoma producing a monoclonal antibody that binds a polypeptide of the invention.

Any of the many well known protocols used for fusing lymphocytes and immortalized cell lines can be applied for the purpose of generating a monoclonal antibody to a polypeptide of the invention (see, e.g., Current Protocols in Immunology, supra; Galfre et al., Nature 266:55052 (1977); R. H. Kenneth, in Monoclonal Antibodies: A New Dimension In Biological Analyses, Plenum Publishing Corp., New York, N.Y. (1980); and Lerner, Yale J. Biol. Med. 54:387-402 (1981)). Moreover, the ordinarily skilled worker will appreciate that there are many variations of such methods that also would be useful.

Alternative to preparing monoclonal antibody-secreting hybridomas, a monoclonal antibody to a polypeptide of the invention can be identified and isolated by screening a recombinant combinatorial immunoglobulin library (e.g., an antibody phage display library) with the polypeptide to thereby isolate immunoglobulin library members that bind the polypeptide. Kits for generating and screening phage display libraries are commercially available (e.g., the Pharmacia Recombinant Phage Antibody System, Catalog No. 27-9400-01; and the Stratagene SurfZAP™ Phage Display Kit, Catalog No. 240612). Additionally, examples of methods and reagents particularly amenable for use in generating and screening antibody display library can be found in, for example, U.S. Pat. No. 5,223,409; PCT Publication No. WO 92/18619; PCT Publication No. WO 91/17271; PCT Publication No. WO 92/20791; PCT Publication No. WO 92/15679; PCT Publication No. WO 93/01288; PCT Publication No. WO 92/01047; PCT Publication No. WO 92/09690; PCT Publication No. WO 90/02809; Fuchs et al., Bio/Technology 9: 1370-1372 (1991); Hay et al., Hum. Antibod. Hybridomas 3:81-85 (1992); Huse et al., Science 246: 1275-1281 (1989); and Griffiths et al., EMBO J. 12:725-734 (1993).

Additionally, recombinant antibodies, such as chimeric and humanized monoclonal antibodies, comprising both human and non-human portions, which can be made using standard recombinant DNA techniques, are within the scope of the invention. Such chimeric and humanized monoclonal antibodies can be produced by recombinant DNA techniques known in the art.

In general, antibodies of the invention (e.g., a monoclonal antibody) can be used to isolate a polypeptide of the invention by standard techniques, such as affinity chromatography or immunoprecipitation. A polypeptide-specific antibody can facilitate the purification of natural polypeptide from cells and of recombinantly produced polypeptide expressed in host cells. Moreover, an antibody specific for a polypeptide of the invention can be used to detect the polypeptide (e.g., in a cellular lysate, cell supernatant, or tissue sample) in order to evaluate the abundance and pattern of expression of the polypeptide. Antibodies can be used diagnostically to monitor protein levels in tissue as part of a clinical testing procedure, e.g., to, for example, determine the efficacy of a given treatment regimen. The antibody can be coupled to a detectable substance to facilitate its detection. Examples of detectable substances include various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, beta-galactosidase, or acetylcholinesterase; examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine fluorescein, dansyl chloride or phycoerythrin; an example of a luminescent material includes luminol; examples of bioluminescent materials include luciferase, luciferin, and aequorin, and examples of suitable radioactive material include ¹²⁵I, ¹³¹I, ³⁵S or ³H.

Antibodies may also be useful in pharmacogenomic analysis. In such embodiments, antibodies against variant proteins encoded by nucleic acids according to the invention, such as variant proteins that are encoded by nucleic acids that contain at least one polymorphic marker of the invention, can be used to identify individuals that require modified treatment modalities.

Antibodies can furthermore be useful for assessing expression of variant proteins in disease states, such as in active stages of a cancer, such as prostate cancer and/or colorectal cancer, or in an individual with a predisposition to a cancer related to the function of the protein, in particular prostate cancer and colorectal cancer. Antibodies specific for a variant protein of the present invention that is encoded by a nucleic acid that comprises at least one polymorphic marker or haplotype as described herein can be used to screen for the presence of the variant protein, for example to screen for a predisposition to prostate cancer and/or colorectal cancer, as indicated by the presence of the variant protein.

Antibodies can be used in other methods. Thus, antibodies are useful as diagnostic tools for evaluating proteins, such as variant proteins of the invention, in conjunction with analysis by electrophoretic mobility, isoelectric point, tryptic or other protease digest, or for use in other physical assays known to those skilled in the art. Antibodies may also be used in tissue typing. In one such embodiment, a specific variant protein has been correlated with expression in a specific tissue type, and antibodies specific for the variant protein can then be used to identify the specific tissue type.

Subcellular localization of proteins, including variant proteins, can also be determined using antibodies, and can be applied to assess aberrant subcellular localization of the protein in cells in various tissues. Such use can be applied in genetic testing, but also in monitoring a particular treatment modality. In the case where treatment is aimed at correcting the expression level or presence of the variant protein or aberrant tissue distribution or developmental expression of the variant protein, antibodies specific for the variant protein or fragments thereof can be used to monitor therapeutic efficacy.

Antibodies are further useful for inhibiting variant protein function, for example by blocking the binding of a variant protein to a binding molecule or partner. Such uses can also be applied in a therapeutic context in which treatment involves inhibiting a variant protein's function. An antibody can be for example be used to block or competitively inhibit binding, thereby modulating (i.e., agonizing or antagonizing) the activity of the protein. Antibodies can be prepared against specific protein fragments containing sites required for specific function or against an intact protein that is associated with a cell or cell membrane. For administration in vivo, an antibody may be linked with an additional therapeutic payload, such as radionuclide, an enzyme, an immunogenic epitope, or a cytotoxic agent, including bacterial toxins (diphtheria or plant toxins, such as ricin). The in vivo half-life of an antibody or a fragment thereof may be increased by pegylation through conjugation to polyethylene glycol.

The present invention further relates to kits for using antibodies in the methods described herein. This includes, but is not limited to, kits for detecting the presence of a variant protein in a test sample. One preferred embodiment comprises antibodies such as a labelled or labelable antibody and a compound or agent for detecting variant proteins in a biological sample, means for determining the amount or the presence and/or absence of variant protein in the sample, and means for comparing the amount of variant protein in the sample with a standard, as well as instructions for use of the kit.

The present invention will now be exemplified by the following non-limiting example.

EXEMPLIFICATION Example 1 Identification of Markers and LD Block Regions Associated with Prostate Cancer

Patients Involved in the Genetics Study

A population based list of all prostate and colorectal cancer patients that were diagnosed in Iceland from 1955 to 2005 form the basis for this study. Patients have been invited to join the study since 2001 on an ongoing basis. As of June 2007, blood samples from 1,850 prostate cancer and 1,169 colorectal cancer patients have been recruited. Genomic DNA from those samples, as well as samples from over 27,000 control individuals was extracted and genotyped.

Genotyping

A genome-wide scan of 1,645 Icelandic individuals diagnosed with Prostate Cancer, 1,010 colorectal cancer patients and 27,049 population controls was performed using Infinium HumanHap300 SNP chips from Illumina for assaying approximately 317,000 single nucleotide polymorphisms (SNPs) on a single chip (Illumina, San Diego, Calif., USA). SNP genotyping for replication in other case-control cohorts was carried using the Centaurus platform (Nanogen).

Statistical Methods for Association and Haplotype Analysis

For single marker association to the disease, Fisher exact test was used to calculate a two-sided P-value for each individual allele. When presenting the results, we used allelic frequencies rather than carrier frequencies for SNPs and haplotypes. The program NEMO (NEsted Models; Gretarsdóttir, et al., Nat Genet. 2003 October; 35(2):131-8) was used both to study marker-marker association and to calculate linkage disequilibrium (LD) between markers. With NEMO, haplotype frequencies are estimated by maximum likelihood and the differences between patients and controls are tested using a generalized likelihood ratio test. The maximum likelihood estimates, likelihood ratios and P-values are computed with the aid of the EM-algorithm directly for the observed data, and hence the loss of information due to the uncertainty with phase and missing genotypes is automatically captured by the likelihood ratios, and under most situations, large sample theory can be used to reliably determine statistical significance. The relative risk (RR) of an allele or a haplotype, i.e., the risk of an allele compared to all other alleles of the same marker, is calculated assuming the multiplicative model (Terwilliger, J. D. & Ott, J. A haplotype-based ‘haplotype relative risk’ approach to detecting allelic associations. Hum. Hered. 42, 337-46 (1992) and Falk, C. T. & Rubinstein, P. Haplotype relative risks: an easy reliable way to construct a proper control sample for risk calculations. Ann. Hum. Genet. 51 (Pt 3), 227-33 (1987)), together with the population attributable risk (PAR). When controls are considered unaffected (i.e., disease-free), the relative risk is replaced by an estimate for the odds ratio (OR) of the particular marker allele or haplotype.

As a measure of LD, we use two standard definitions of LD, D′ and R² (Lewontin, R., Genetics, 49:49-67 (1964) and Hill, W. G. and A. Robertson, Theor. Appl. Genet., 22:226-231 (1968)) as they provide complementary information on the amount of LD. For the purpose of estimating D′ and R², the frequencies of all two-marker allele combinations are estimated using maximum likelihood methods and the deviation from linkage disequilibrium is evaluated using a likelihood ratio test. The standard definitions of D′ and R² are extended to include microsatellites by averaging over the values for all possible allele combinations of the two markers weighted by the marginal allele probabilities.

Results

Through analysis of over 300,000 markers across the genome, we identified two regions that are associated with prostate and colorectal cancer. In Table 1, we show results of association of markers rs10896450 and rs7947353 on Chr 11q13.3 to prostate cancer. The two markers are fully correlated (D′=1 and r²=1; see footnote of Table 1) and do therefore essentially represent the same association signal The G allele of SNP marker rs10896450 confers increased risk of prostate cancer, with an odds ratio (OR) of 1.17 in the Icelandic samples (P=6.6×10⁻⁵).

To validate the initial discovery, we attempted to genotype the rs10896450 SNP marker in prostate cancer cohorts from the Netherlands, Spain and US (Chicago, Ill.). However, the design of the Centaurus assay failed for this marker and we therefore selected a fully correlated SNP rs7947353 (D′=1 and r²=1; see footnote of Table 1) for further genotyping and analysis in the replication samples. The results for allele A of SNP marker rs7947353 from the replication cohorts are shown in Table 1, and are comparable to the results for the Icelandic discovery cohort. The observed risk in the Spanish cohort is somewhat lower than in Iceland, while the US cohort has a higher risk. Overall, the association is significant with a p-value of 1.43×10⁶.

A second association signal was detected on Chromosome 6 for prostate cancer (Table 2a). The signal was replicated in Dutch and Spanish cohort, both which gave increased risk conferred by the G allele of the rs10943605 SNP marker, although only the replication in the Dutch cohort is statistically significant. The G allele of the rs10943605 SNP marker was also found to be associated with increased risk of developing colorectal cancer, with an OR of 1.14 in the Icelandic colorectal cancer samples (P=4.8×10⁻³) (Table 2b).

TABLE 1 Association results for 11q13.3 and prostate cancer in Iceland discovery cohort, and replication cohorts from The Netherlands, Spain, and the US Study population (N cases/N controls) Frequency Variant (allele) Cases Controls OR P value Iceland(1,645/21,474) rs10896450 (G)^(a) 0.505 0.466 1.17 6.6 × 10⁻⁵ rs7947353 (A)^(a) 0.505 0.466 1.17 6.6 × 10⁻⁵ The Netherlands (998/2,014) rs7947353 (A) 0.528 0.500 1.12 0.042 Spain (455/1,066) rs7947353 (A) 0.579 0.564 1.06 0.450 Chicago, Illinois (661/292) rs7947353 (A) 0.545 0.493 1.23 0.035 All above combined (3,759/24,846) rs7947353 (A) — 0.506 1.15 1.43 × 10⁻⁶ ^(a)Correlation between the two markers see below (results are based on analysis of 2,340 Icelanders: M1 M2 D′ r² rs10896450 rs7947353 1 1

TABLE 2a Association results for 6q14.1 and prostate cancer in Icelandic discovery cohorts, and replication cohorts from The Netherlands and Spain. Study population (N cases/N controls) Frequency Variant (allele) Cases Controls OR P value Iceland PrCa (1,645/21,472) rs10943605 (G) 0.597 0.557 1.18 2.72 × 10⁻⁵ The Netherlands PrCa (910/2,006) rs10943605 (G) 0.530 0.490 1.17 6.04 × 10⁻³ Spain PrCa (436/1,417) rs10943605 (G) 0.567 0.553 1.06 0.480 All above combined (2,991/24,895) rs10943605 (G) — 0.533 1.16 9.35 × 10⁻⁷

TABLE 2b Association results for 6q14.1 and colorectal cancer in Iceland Study population (N cases/N controls) Frequency Variant (allele) Cases Controls OR P value Iceland ColCa (1,010/27,033) rs10943605 (G) 0.591 0.558 1.14 4.8 × 10⁻³

TABLE 3 SNP markers that are in linkage disequilibrium with marker rs10943605 on Chromosome 6. Marker 1 Marker 1 Marker 2 D′ r² p-value location Seq ID No: rs611737 rs10943605 0.631963 0.293866 3.91E−09 79300773 1 rs666982 rs10943605 0.605842 0.284949 6.11E−09 79316431 2 rs685245 rs10943605 0.606322 0.29663 1.77E−08 79327502 3 rs547472 rs10943605 0.608391 0.291941 4.51E−09 79341083 4 rs654628 rs10943605 0.603324 0.288712 6.47E−09 79343805 5 rs605697 rs10943605 0.622444 0.296062 6.91E−09 79345910 6 rs605264 rs10943605 0.605842 0.284949 6.11E−09 79346003 7 rs603964 rs10943605 0.609097 0.293439 6.80E−09 79346271 8 rs612489 rs10943605 0.604036 0.290201 9.72E−09 79346309 9 rs484582 rs10943605 0.610497 0.30416 4.78E−09 79346824 10 rs597283 rs10943605 0.572594 0.27296 3.74E−08 79347449 11 rs596810 rs10943605 0.590052 0.272681 2.36E−08 79347562 12 rs596337 rs10943605 0.600542 0.282979 1.11E−08 79347676 13 rs655566 rs10943605 0.597614 0.277093 1.90E−08 79348564 14 rs689389 rs10943605 0.608391 0.291941 4.51E−09 79348661 15 rs846452 rs10943605 0.60564 0.286192 7.77E−09 79348887 16 rs674105 rs10943605 0.605842 0.284949 6.11E−09 79349688 17 rs236867 rs10943605 0.605842 0.284949 6.11E−09 79355383 18 rs236872 rs10943605 0.593491 0.304327 7.89E−09 79358008 19 rs236873 rs10943605 0.592785 0.282009 1.33E−08 79358580 20 rs236877 rs10943605 0.608391 0.291941 4.51E−09 79362203 21 rs70478 rs10943605 0.564166 0.209862 3.01E−06 79364899 22 rs70480 rs10943605 0.568404 0.216181 1.39E−06 79365324 23 rs236882 rs10943605 0.695923 0.256498 5.08E−08 79372832 24 rs236884 rs10943605 0.700831 0.26597 3.12E−08 79376244 25 rs236888 rs10943605 0.741063 0.286153 1.20E−08 79378960 26 rs236861 rs10943605 0.689267 0.264436 2.73E−07 79390866 27 rs236862 rs10943605 0.65937 0.248439 1.40E−07 79391691 28 rs236855 rs10943605 0.74615 0.29984 5.25E−09 79398610. 29 rs12210702 rs10943605 0.886957 0.355449 2.28E−11 79426052 30 rs9359338 rs10943605 0.897621 0.450682 1.86E−13 79453470 31 rs9352611 rs10943605 0.89472 0.436416 7.36E−13 79453687 32 rs10943567 rs10943605 0.901397 0.4471 6.06E−14 79459170 33 rs10943568 rs10943605 0.898063 0.444367 5.16E−13 79460926 34 rs9343786 rs10943605 0.901397 0.4471 6.06E−14 79471447 35 rs4706718 rs10943605 0.901397 0.4471 6.06E−14 79473602 36 rs9341739 rs10943605 0.899434 0.433323 2.58E−13 79475795 37 rs9352613 rs10943605 0.901397 0.4471 6.06E−14 79481152 38 rs13198615 rs10943605 0.620748 0.264225 2.31E−08 79487271 39 rs1180823 rs10943605 0.786316 0.274692 3.17E−09 79489645 40 rs1180828 rs10943605 0.620748 0.264225 2.31E−08 79492141 41 rs9343798 rs10943605 0.620748 0.264225 2.31E−08 79512001 42 rs7382016 rs10943605 0.620748 0.264225 2.31E−08 79512500 43 rs7759829 rs10943605 1 0.257426 5.01E−10 79513725 44 rs7759687 rs10943605 0.910286 0.229805 3.16E−07 79513734 45 rs9361426 rs10943605 0.620748 0.264225 2.31E−08 79514269 46 rs1158575 rs10943605 0.620748 0.264225 2.31E−08 79515925 47 rs9359344 rs10943605 0.620748 0.264225 2.31E−08 79517752 48 rs4141594 rs10943605 0.502039 0.207557 9.50E−07 79517914 49 rs9343820 rs10943605 1 0.87395 2.70E−31 79537177 50 rs1876389 rs10943605 0.824869 0.421093 3.32E−13 79538651 51 rs1021987 rs10943605 1 0.21875 2.66E−09 79539884 52 rs1507152 rs10943605 0.83431 0.329234 2.01E−10 79540193 53 rs1507153 rs10943605 1 0.509466 2.18E−18 79541105 54 rs9343824 rs10943605 1 0.537205 1.54E−18 79554288 55 rs1507149 rs10943605 0.960507 0.683059 4.95E−22 79556805 56 rs9343827 rs10943605 1 0.967033 1.10E−35 79557755 57 rs6926463 rs10943605 0.942137 0.382849 1.82E−12 79559890 58 rs9361448 rs10943605 1 0.300546 1.55E−11 79579645 59 rs12195716 rs10943605 1 0.967033 1.10E−35 79592131 60 rs6902294 rs10943605 1 0.21875 2.66E−09 79593001 61 rs1567168 rs10943605 1 0.967033 1.10E−35 79593174 62 rs2135767 rs10943605 0.943831 0.389733 6.65E−13 79593386 63 rs9352662 rs10943605 0.939889 0.390142 2.32E−11 79598210 64 rs1027813 rs10943605 1 1 1.22E−37 79608837 65 rs1567167 rs10943605 1 1 1.14E−36 79610546 66 rs12196485 rs10943605 1 0.550265 1.01E−19 79613590 67 rs9352663 rs10943605 1 0.550265 1.01E−19 79614883 68 rs971994 rs10943605 1 1 9.93E−37 79616321 69 rs4421161 rs10943605 1 1 6.05E−38 79620938 70 rs12176511 rs10943605 1 0.715909 1.15E−25 79622440 71 rs9352664 rs10943605 1 1 6.05E−38 79622881 72 rs9352666 rs10943605 1 1 2.00E−36 79628903 73 rs9352667 rs10943605 1 1 6.05E−38 79629015 74 rs9352668 rs10943605 1 0.715909 2.11E−25 79629397 75 rs9448584 rs10943605 1 1 6.05E−38 79629518 76 rs9361459 rs10943605 1 0.715909 7.04E−25 79629641 77 rs9341753 rs10943605 1 0.361702 6.05E−14 79634515 78 rs9352669 rs10943605 1 1 2.00E−36 79640860 79 rs9341754 rs10943605 1 0.966443 8.10E−35 79641692 80 rs9343844 rs10943605 1 1 1.30E−37 79643182 81 rs9350792 rs10943605 1 0.550265 1.01E−19 79643892 82 rs9361460 rs10943605 1 1 6.05E−38 79646186 83 rs9359354 rs10943605 1 1 8.67E−36 79647104 84 rs2174743 rs10943605 1 1 1.30E−37 79648524 85 rs6908105 rs10943605 1 0.516024 7.87E−19 79651816 86 rs12192086 rs10943605 1 0.360294 5.04E−14 79657229 87 rs2174742 rs10943605 1 1 1.22E−37 79666820 88 rs9352675 rs10943605 1 1 2.30E−37 79669519 89 rs1354832 rs10943605 1 0.966849 1.92E−35 79670482 90 rs4706079 rs10943605 1 1 2.00E−36 79671927 91 rs7756858 rs10943605 1 1 2.45E−37 79676687 92 rs9448594 rs10943605 1 0.355054 2.69E−12 79679933 93 rs12196457 rs10943605 1 0.550265 1.01E−19 79684462 94 rs9343853 rs10943605 1 0.375 1.67E−14 79699300 95 rs7740307 rs10943605 1 0.525 2.34E−19 79710873 96 rs10943605 rs10943605 1 1 — 79712196 97 rs2275291 rs10943605 1 0.351955 9.65E−13 79713281 98 rs2275290 rs10943605 1 0.525 3.77E−19 79713289 99 rs1984195 rs10943605 1 1 1.30E−37 79714110 100 rs2174739 rs10943605 1 1 1.14E−37 79715889 101 rs9448600 rs10943605 1 0.525 2.34E−19 79719788 102 rs3805746 rs10943605 1 0.525 3.77E−19 79729157 103 rs3805747 rs10943605 1 1 1.22E−37 79729241 104 rs10943608 rs10943605 1 0.565217 6.62E−20 79731648 105 rs9350797 rs10943605 1 0.360294 5.04E−14 79732420 106 rs11964204 rs10943605 1 0.525 2.34E−19 79732781 107 rs9343856 rs10943605 1 1 1.30E−37 79734930 108 rs1538235 rs10943605 1 1 7.59E−37 79746169 109 rs1572584 rs10943605 1 1 6.05E−38 79747009 110 rs1572585 rs10943605 1 1 3.77E−36 79747295 111 rs1890229 rs10943605 1 1 6.05E−38 79751748 112 rs3818839 rs10943605 1 0.380941 1.44E−14 79757044 113 rs9359360 rs10943605 1 0.575195 7.14E−19 79759515 114 rs9359361 rs10943605 1 0.367498 1.07E−13 79762302 115 rs9361477 rs10943605 1 0.558824 9.59E−20 79767525 116 rs9448607 rs10943605 1 0.757211 5.03E−26 79772339 117 rs9352683 rs10943605 1 1 4.94E−36 79775514 118 rs9443638 rs10943605 1 1 2.00E−36 79777586 119 rs4706747 rs10943605 1 1 1.30E−37 79779358 120 rs9361480 rs10943605 1 1 2.89E−34 79781148 121 rs1338023 rs10943605 1 0.365871 4.42E−14 79785047 122 rs2050660 rs10943605 1 1 6.05E−38 79791445 123 rs9448610 rs10943605 1 0.733202 5.86E−26 79796341 124 rs1538233 rs10943605 1 1 6.05E−38 79800454 125 rs9343861 rs10943605 1 0.509466 2.18E−18 79801587 126 rs10943613 rs10943605 1 0.740385 5.66E−26 79801826 127 rs11758432 rs10943605 1 0.375 1.67E−14 79806313 128 rs9361482 rs10943605 1 0.733202 2.00E−25 79807104 129 rs9343863 rs10943605 1 1 6.05E−38 79809511 130 rs2050663 rs10943605 1 1 2.30E−37 79810113 131 rs9448616 rs10943605 1 0.360294 5.04E−14 79813653 132 rs9352686 rs10943605 1 1 2.45E−37 79814942 133 rs2152951 rs10943605 1 1 6.05E−38 79818891 134 rs9343865 rs10943605 1 0.368421 4.53E−14 79821914 135 rs9343867 rs10943605 1 0.364105 5.50E−14 79829072 136 rs1547731 rs10943605 1 1 1.14E−37 79832823 137 rs9352688 rs10943605 1 0.360294 5.04E−14 79832882 138 rs10455120 rs10943605 1 0.444999 1.18E−15 79836486 139 rs9343869 rs10943605 1 0.360294 7.16E−14 79841140 140 rs9352691 rs10943605 1 0.550265 1.01E−19 79842326 141 rs7753531 rs10943605 1 0.709974 7.37E−25 79846715 142 rs7776138 rs10943605 1 0.375 1.67E−14 79851212 143 rs9359364 rs10943605 0.947194 0.482034 1.37E−13 79852711 144 rs9352693 rs10943605 1 0.352274 3.20E−13 79854791 145 rs7767100 rs10943605 0.964821 0.930648 1.26E−29 79867252 146 rs9443644 rs10943605 0.937107 0.333308 3.02E−11 79867363 147 rs12197385 rs10943605 1 0.266602 4.88E−10 79872695 148 rs9361489 rs10943605 0.965965 0.933016 1.07E−31 79873504 149 rs949846 rs10943605 0.950814 0.497465 6.74E−16 79874315 150 rs6916081 rs10943605 0.941241 0.345568 4.80E−12 79874571 151 rs1415310 rs10943605 0.856953 0.419639 3.80E−13 79879033 152 rs9443645 rs10943605 0.931848 0.839777 1.03E−27 79879643 153 rs10943616 rs10943605 0.853077 0.40045 1.48E−12 79880260 154 rs6940949 rs10943605 0.876626 0.288616 1.29E−09 79880754 155 rs7768535 rs10943605 0.930436 0.292034 1.28E−09 79892231 156 rs3920791 rs10943605 0.869223 0.261765 6.14E−09 79893453 157 rs1361043 rs10943605 0.873498 0.269641 3.81E−09 79893786 158 rs9343876 rs10943605 0.806769 0.225158 1.01E−07 79901219 159 rs9352701 rs10943605 0.876903 0.28836 1.27E−09 79916596 160 rs9361497 rs10943605 0.876903 0.28836 1.27E−09 79916649 161 rs9294130 rs10943605 0.746969 0.282652 8.22E−09 79917888 162 Linkage disequilibrium was calculated based on HapMap CEU population data (http://www.hapmap.org). Location of correlated markers is given with respect to NCBI Build 36 of the Human genome assembly.

TABLE 4 SNP markers that are in linkage disequilibrium with marker rs10896450 on Chromosome 11. Linkage disequilibrium was calculated based on HapMap CEU population data (http://www.hapmap.org). Location of correlated markers is given with respect to NCBI Build 36 of the Human genome assembly. Marker 1 Seq ID Pos in Seq Marker 1 Marker 2 D′ r² p-value location No: ID: 201 rs7128814 rs10896450 0.754033 0.328273 7.44E−09 68709630 163 300 rs10896444 rs10896450 0.950801 0.522291 5.93E−15 68723823 164 14493 rs10896445 rs10896450 0.951635 0.522873 3.85E−15 68724217 165 14887 rs4255548 rs10896450 1 0.620339 2.97E−22 68730546 166 21216 rs7117034 rs10896450 1 0.257642 2.43E−10 68731718 167 22388 rs4495900 rs10896450 1 0.606213 5.17E−21 68732695 168 23365 rs11228563 rs10896450 1 0.373812 1.43E−13 68733572 169 24242 rs12281017 rs10896450 1 0.295093 8.65E−11 68734077 170 24747 rs11228565 rs10896450 1 0.249586 7.96E−10 68735156 171 25826 rs4620729 rs10896450 1 1 4.70E−38 68736911 172 27581 rs11821008 rs10896450 1 0.329609 1.51E−12 68737211 173 27881 rs11825796 rs10896450 1 0.311982 7.96E−12 68737364 174 28034 rs4451736 rs10896450 1 0.964531 2.83E−34 68739279 175 29949 rs12278923 rs10896450 1 0.959809 3.04E−31 68740137 176 30807 rs7929962 rs10896450 1 1 4.70E−38 68742159 177 32829 rs7109672 rs10896450 1 0.967195 8.12E−36 68747686 178 38356 rs10896448 rs10896450 1 1 4.70E−38 68748325 179 38995 rs12795301 rs10896450 1 0.241803 5.99E−10 68748861 180 39531 rs7122190 rs10896450 1 0.967195 8.12E−36 68750364 181 41034 rs6591374 rs10896450 1 1 1.90E−37 68750408 182 41078 rs7931342 rs10896450 1 0.967195 1.58E−35 68751073 183 41743 rs10896449 rs10896450 1 1 4.70E−38 68751243 184 41913 rs7130881 rs10896450 1 0.241803 5.99E−10 68752534 185 43204 rs12362678 rs10896450 1 0.967195 8.12E−36 68752746 186 43416 rs9787877 rs10896450 1 1 4.70E−38 68753085 187 43755 rs11603288 rs10896450 1 0.242151 1.13E−09 68753358 188 44028 rs4644650 rs10896450 1 0.967195 8.12E−36 68754694 189 45364 rs7950547 rs10896450 0.953052 0.582711 4.00E−15 68755364 190 46034 rs11228580 rs10896450 1 0.229339 1.58E−09 68758918 191 49588 rs7939250 rs10896450 1 1 1.87E−37 68759526 192 50196 rs7106762 rs10896450 1 1 4.70E−38 68760282 193 50952 rs12417087 rs10896450 1 0.221577 3.17E−09 68760555 194 51225 rs11228581 rs10896450 1 0.337143 7.39E−13 68760586 195 51256 rs7947353 rs10896450 1 1 1.19E−35 68761559 196 52229 rs10896450 rs10896450 1 1 — 68764690 197 55360 rs11228583 rs10896450 1 0.965547 6.06E−35 68765690 198 56360 rs12799883 rs10896450 1 1 1.90E−37 68767227 199 57897 rs3884627 rs10896450 1 0.425723 6.96E−16 68782375 200 73045

TABLE 5 Polymorphic markers within the C11 region, between position 68,709,630 and 68,782,375 in NCBI Build 36. Shown is marker ID (rs-names), position in Build 36, strand and polymorphism type, where (—/N), N being any one nucleotide, or a plurality of nucleotides, corresponding to an insertion/ deletion polymorphism (i.e. either the nucleotide(s) is present or not). Position Marker ID Build 36 Strand Polymorphism rs7128814 68709630 + A/G rs34033330 68709734 + —/T rs4993568 68709920 + G/T rs4993567 68709926 + C/G rs11228548 68710333 + C/T rs11228549 68710384 + C/T rs10896441 68710484 + A/G rs10792027 68710514 + C/G rs10792028 68710515 + C/T rs11228550 68710833 + C/T rs12294054 68711092 + A/G rs11228551 68711570 + A/T rs11228552 68711592 + C/T rs10219207 68713596 + A/G rs12809032 68713686 + C/T rs11606280 68713966 + A/G rs35691765 68715000 + —/G rs4495899 68715236 + G/T rs12800787 68715895 + C/T rs4930664 68715976 + A/G rs4930665 68715984 + A/T rs4072598 68716265 − G/T rs11228553 68716760 + G/T rs10896442 68716789 + A/G rs12223972 68716967 + A/G rs12796709 68719501 + A/C rs34461339 68719872 + —/G rs12803641 68720487 + C/T rs12808650 68720536 + C/G rs12808185 68720581 + A/C rs12808690 68720599 + C/G rs12808846 68720638 + C/G rs12808599 68720804 + A/T rs12808603 68720810 + A/T rs12785256 68720824 + A/G rs11228554 68720854 + C/T rs11602052 68721150 + C/G rs11433399 68721158 + —/G rs10896443 68722211 + G/T rs11228555 68722341 + C/T rs10792029 68723458 + A/G rs4930666 68723812 + C/T rs10896444 68723823 + A/C rs34531633 68724028 + G/T rs11228556 68724029 + G/T rs10896445 68724217 + C/T rs11228557 68724542 + A/G rs10792030 68725391 + A/G rs12417971 68726384 + C/T rs11383798 68726876 + —/G rs7126286 68726993 + C/T rs34210900 68727006 + —/G rs3934653 68727096 − A/C rs12049842 68727624 + G/T rs9783326 68727749 + C/T rs7927331 68729100 + A/G rs7930375 68729233 + C/G rs7945442 68729323 + C/T rs9783278 68729551 + A/C rs9783279 68729568 + A/C rs9783280 68729612 + A/G rs11824548 68729893 + A/G rs7934295 68730254 + C/T rs4255548 68730546 + A/G rs7483742 68730628 + G/T rs7949811 68730632 + G/T rs12792553 68730645 + A/C rs12792562 68730662 + A/C rs12793009 68730931 + C/T rs12793759 68731131 + A/G rs9943593 68731168 + A/G rs11228558 68731439 + C/T rs10896446 68731695 + C/T rs7117034 68731718 + C/T rs11228559 68731861 + C/T rs11228560 68731965 + C/T rs7926098 68732100 + C/T rs12287117 68732101 + C/G rs7942465 68732362 + C/T rs11228561 68732444 + C/G rs7929389 68732558 + A/T rs4495900 68732695 + C/T rs11228562 68732747 + G/T rs11228563 68733572 + A/G rs10792031 68733592 + A/G rs12418968 68733711 + C/T rs12281017 68734077 + A/G rs4930667 68734625 + C/T rs12422130 68734751 + A/G rs11228564 68735154 + C/T rs11228565 68735156 + A/G rs4357697 68735224 + G/T rs7926037 68735253 + C/G rs11228566 68735849 + C/T rs11228567 68736126 + A/G rs7937094 68736282 + C/T rs11228568 68736438 + G/T rs11228569 68736819 + C/T rs4620729 68736911 + A/C rs11821008 68737211 + A/G rs11825791 68737337 + C/G rs11825796 68737364 + A/G rs4930668 68737404 + G/T rs10896447 68737451 + A/C rs4265599 68737642 + A/T rs12275055 68737935 + A/G rs4268514 68738060 + C/G rs28613836 68738536 + C/T rs9665814 68738604 + C/T rs4930669 68738956 + C/T rs4451736 68739279 + A/G rs5792471 68739686 + —/C rs4988608 68739767 + A/G rs4988607 68739830 + G/T rs12278923 68740137 + A/C rs7939803 68740276 + C/T rs10792032 68741178 + A/G rs12294067 68741228 + A/G rs11421935 68741320 + —/G rs11228570 68741410 + C/T rs11228571 68741445 + C/T rs11351679 68742057 + —/T rs7929962 68742159 + C/T rs12282709 68742244 + A/C rs28686842 68742981 + C/G rs12790802 68743071 + A/C rs11824985 68743246 + A/G rs12785252 68743916 + A/C rs12785424 68743958 + A/C rs7941085 68744228 + G/T rs11228572 68744280 + A/G rs7119440 68744363 + A/G rs35024453 68744479 + —/T rs7119681 68744563 + A/G rs7945227 68745639 + A/G rs10792033 68745774 + A/G rs28706904 68746828 + C/T rs35911114 68746864 + —/A rs7121816 68746871 + G/T rs34326593 68746958 + —/C rs7109672 68747686 + A/G rs12270972 68748240 + A/G rs10896448 68748325 + C/G rs34655741 68748385 + —/T rs35960410 68748742 + —/A rs12795301 68748861 + A/C rs11228573 68749659 + G/T rs11228574 68750098 + A/T rs35007842 68750196 + —/G rs7122190 68750364 + C/T rs6591374 68750408 + A/G rs28367011 68750751 + C/T rs36082692 68751072 + —/G rs7931342 68751073 + G/T rs10896449 68751243 + A/G rs10750845 68751541 + A/G rs35730578 68751818 + —/TG rs11228575 68751854 + A/G rs12365199 68751856 + A/G rs11228576 68752122 + A/G rs7130881 68752534 + A/G rs12362678 68752746 + C/G rs11603219 68753019 + A/G rs9787877 68753085 + C/T rs11603288 68753358 + A/G rs11228577 68753390 + C/T rs4644650 68754694 + C/T rs5792472 68754765 + —/G rs4569015 68754981 + C/T rs7950547 68755364 + C/T rs7935842 68755540 + G/T rs4576823 68755685 + A/G rs35572423 68755750 + —/A rs7931312 68757543 + A/G rs34699416 68757796 + —/C rs4930670 68757828 + C/T rs11605287 68758302 + G/T rs11228579 68758793 + G/T rs11228580 68758918 + C/T rs7925434 68759208 + A/T rs7939151 68759472 + A/G rs7939250 68759526 + A/G rs7118074 68759999 + G/T rs12788188 68760157 + A/T rs7106762 68760282 + C/T rs34000592 68760510 + —/T rs12417087 68760555 + A/T rs11228581 68760586 + C/T rs9667638 68760915 + A/T rs28852414 68761492 + A/G rs28876082 68761493 + G/T rs7947353 68761559 + A/G rs7947298 68761677 + A/C rs11826508 68762658 + A/G rs34384086 68763007 + —/C rs36091743 68763507 + —/T rs11228582 68763813 + A/T rs7104671 68763950 + C/G rs12802068 68764310 + A/G rs12802553 68764311 + A/G rs36101702 68764356 + —/TT rs10896450 68764690 + A/G rs12808564 68765268 + A/G rs11228583 68765690 + G/T rs11228584 68766043 + A/G rs10560769 68766333 + —/TT rs12293259 68766814 + G/T rs12799883 68767227 + G/T rs4451737 68767444 + C/T rs3925012 68767493 + C/T rs4131929 68768714 − C/T rs12270641 68768820 + A/T rs35310215 68769540 + —/G rs35836017 68769588 + —/C rs34255287 68769711 + A/G rs7127508 68770593 + C/T rs7111780 68770972 + A/G rs7111993 68771116 + A/G rs7112311 68771118 + A/G rs11603876 68771837 + A/T rs12282656 68772304 + A/G rs7119988 68772447 + A/G rs36031129 68772686 + —/CC rs11404080 68773007 + —/T rs35921293 68773009 + —/T rs10896451 68773469 + A/C rs34887827 68774015 + C/T rs12420858 68774110 + C/G rs11228585 68774254 + C/T rs10530250 68774509 + (LARGE DELETION)/— rs11228586 68774667 + C/T rs11228587 68774847 + A/G rs4930671 68774950 + A/G rs10896452 68775074 + C/T rs11606813 68775164 + C/T rs12225965 68775407 + A/G rs34717487 68775561 + G/T rs4930672 68775807 + A/G rs12293276 68775830 + A/G rs7118966 68775848 + C/T rs7102758 68775981 + A/G rs12421619 68775992 + C/T rs35400111 68776233 + —/G rs11228588 68776545 + A/G rs34223044 68776551 + —/C rs11828682 68776692 + A/G rs7118204 68777260 + A/G rs12806580 68777418 + C/T rs35349840 68777566 + —/G rs10896453 68777614 + A/G rs10792034 68777793 + C/T rs4531476 68778231 + C/G rs11228589 68778253 + A/G rs11228590 68778283 + C/T rs11228591 68779388 + A/C rs35087861 68779558 + —/G rs11228593 68779604 + A/G rs11228594 68779663 + A/G rs11228595 68779946 + C/T rs7127913 68780032 + C/G rs10736673 68780073 + C/T rs11228596 68780341 + A/G rs11228597 68780850 + A/G rs36061232 68781372 + —/A rs11602505 68781617 + C/G rs7928306 68781639 + C/T rs11228598 68781757 + A/G rs7121952 68781886 + C/T rs12792211 68782129 + A/G rs7122303 68782158 + C/T rs3884627 68782375 − A/C

TABLE 6 Polymorphic markers within the C06 region, between position 79,300,773 and 79,917,888 in NCBI Build 36. Shown is marker ID (rs-names), position in Build 36, strand and polymorphism type, where (—/N), N being any nucleotide or a plurality of nucleotides, corresponding to an insertion/deletion polymorphism (i.e. either the nucleotide(s) is present or not, as indicated). Position Marker ID Build 36 Strand Polymorphism rs611737 79300773 + A/T rs626819 79301359 + A/G rs6910813 79302376 + C/T rs12214422 79302660 + A/G rs644560 79303061 + C/T rs9352604 79303344 + A/G rs9448457 79303808 + C/T rs686492 79305307 + C/T rs9448458 79305343 + A/G rs6929235 79305516 + C/T rs34452249 79305637 + —/A rs7749430 79305957 + A/G rs817878 79306182 + C/T rs9443588 79306226 + A/G rs9448459 79306228 + A/G rs7749697 79306342 + C/T rs768590 79306749 + C/T rs9448460 79306888 + A/G rs35921129 79307666 + —/G rs586228 79308383 + C/T rs34460368 79308541 + —/C rs680095 79309251 + G/T rs36120289 79309395 + —/T rs681322 79309441 + A/G rs681802 79309548 + A/C rs36181646 79310146 + —/T rs7742933 79310346 + C/G rs7742862 79310526 + A/T rs34040490 79311019 + —/A rs9359329 79311380 + C/T rs9294118 79311509 + A/T rs9341737 79311928 + G/T rs9443589 79312030 + C/G rs1506767 79312288 + A/C rs9448462 79312500 + A/G rs9359330 79312505 + C/T rs817881 79312760 + A/T rs9448463 79312774 + A/G rs817882 79312776 + A/G rs4321794 79312812 + A/G rs817883 79313522 + C/G rs9448464 79313952 + A/C rs590624 79314042 − A/C rs9448465 79314256 + A/C rs34720156 79314273 + —/C/T rs9443590 79314631 + A/G rs587503 79314716 − C/G rs9448466 79315160 + A/G rs682852 79315205 + A/T rs9443591 79315537 + C/T rs12183583 79315477 + C/T rs12202264 79315943 + A/G rs9443592 79316009 + A/G rs35257893 79316335 + —/C rs666982 79316431 + C/T rs9443593 79316432 + C/T rs34323328 79316810 + —/T rs654652 79316879 + G/T rs12528215 79316955 + A/C rs34348581 79317371 + —/A rs652356 79317426 + A/T rs651900 79317529 − G/T rs651894 79317535 − G/T rs10565029 79317635 + —/AAA rs10590702 79317656 + —/AAA rs17823349 79318539 + C/T rs35611717 79319004 + —/TTT rs2024994 79319262 + C/T rs34242911 79319291 + —/A rs6932288 79319758 + G/T rs16890129 79319993 + C/T rs600913 79320040 + C/T rs1625514 79320259 + C/T rs10611862 79320291 + —/AC rs10695566 79320376 + —/C/T/TA rs28652972 79320377 + C/T rs34108696 79320377 + —/TA rs13214614 79320385 + C/G rs13214617 79320392 + A/G rs817886 79320395 + —/A/G/GT rs28736801 79320394 + A/G rs13214437 79320413 + C/T rs13214632 79320425 + C/G rs12200116 79320434 + A/G rs12213654 79320441 + C/T rs13200111 79320447 + C/T rs9341738 79320646 + G/T rs1616969 79320658 − A/C rs12215356 79320880 + A/G rs3063781 79321086 + —/GATA rs616011 79321162 + C/T rs685093 79321296 + C/T rs1321599 79321507 + C/T rs12195790 79321512 + A/T rs12215690 79321527 + A/G rs9448467 79321532 + A/G rs10214428 79321604 + A/G rs5877614 79321661 + —/ATGT rs35273466 79321666 + —/TGTA rs10214574 79321924 + C/T rs12203729 79321949 + A/G rs653092 79322088 − A/G rs34332845 79322089 + CA/TG rs653091 79322089 − C/T rs12190592 79322474 + C/T rs669241 79322487 − C/T rs13328234 79322502 + C/T rs11963866 79322524 + A/T rs668305 79322704 − A/G rs9448468 79322719 + C/T rs656825 79322983 − A/T rs656806 79322991 − C/T rs656767 79323027 − C/T rs636717 79323460 − C/T rs623155 79324200 − A/G rs1588045 79324435 − A/G rs1588044 79324438 − A/G rs12154026 79324811 + C/T rs36029617 79324861 + A/C rs627261 79324993 − A/T rs9448469 79325158 + A/T rs12196214 79325431 + C/T rs625065 79325534 + C/T rs625051 79325550 + G/T rs623658 79325869 − A/G rs611493 79326235 + A/G rs34644016 79326358 + —/C rs7762380 79326371 + C/T rs2063044 79327042 − A/G rs2057299 79327290 + C/T rs685245 79327502 + G/T rs9443594 79327549 + A/G rs594889 79327616 + —/A/T rs2321446 79328223 + C/G rs2321447 79328224 + C/T rs9294119 79328300 + A/G rs12200457 79328690 + G/T rs675860 79328980 − C/T rs1395451 79329158 − A/C rs5877615 79329487 + —/AG rs33932619 79329488 + —/AG rs2307940 79329492 − —/TC rs9448471 79329660 + C/T rs627504 79329799 − C/T rs817874 79329815 − A/T rs34927882 79330116 + —/C rs4532413 79330118 + A/G rs7755570 79330301 + A/G rs624930 79330391 − A/G rs7755650 79330536 + A/C rs11321290 79330606 + —/A rs4055943 79330613 + —/AA rs5877616 79330615 + —/A/AA rs623900 79330662 + A/C rs35720273 79331059 + A/T rs9448472 79331128 + C/T rs1354783 79331316 − A/G rs9448473 79332278 + A/C rs9448474 79332375 + A/G rs9448475 79332618 + C/T rs10485132 79333000 − A/G rs9448476 79333023 + G/T rs9361409 79333075 + C/T rs6936674 79333218 + A/C rs599356 79333269 + C/G rs9448477 79333362 + C/G rs35610189 79333362 + —/C rs9350762 79333552 + C/T rs35356866 79333742 + —/A rs9443595 79333782 + C/T rs817873 79333940 + A/C rs34056090 79334129 + —/G rs35568407 79334141 + —/C rs35329543 79334333 + —/G rs1180729 79334524 + A/T rs12203331 79334532 + C/T rs11966608 79335281 + C/T rs12527974 79335652 + C/T rs2321448 79335824 + A/C rs4357091 79335896 + A/T rs35401847 79336555 + —/A rs34962042 79336668 + —/G rs34243415 79336793 + —/C rs660115 79336811 − A/G rs665915 79336879 + C/T rs2321449 79337577 + A/C rs10214706 79337707 + A/G rs645217 79337828 − C/T rs9448478 79338056 + A/T rs1180712 79339059 + G/T rs34586728 79339119 + A/C rs34371761 79339519 + —/A rs5877617 79339832 + —/C rs12202205 79340216 + C/T rs2022199 79340391 − C/T rs5877618 79340404 + —/A rs34256059 79340405 + —/A rs5877619 79340411 + —/A rs35771902 79340412 + —/A rs2022198 79340494 − C/T rs615980 79340588 + C/T rs35269485 79340618 + —/A rs2022197 79340630 − C/T rs616526 79340734 + A/G rs547472 79341083 + C/T rs4706714 79341084 + A/C rs9448479 79341414 + C/T rs671940 79342180 − C/T rs2321450 79342370 + C/G rs662430 79342674 + C/T rs12214043 79342882 + A/T rs34757416 79342885 + —/CA rs1853111 79342888 + C/T rs34922104 79342890 + —/TT rs12207739 79342893 + A/T rs28643317 79342897 + A/T rs28498695 79342903 + A/T rs28394665 79342909 + A/T rs10455117 79342926 + A/T rs474764 79342934 + G/T rs28436215 79342992 + A/C rs10455118 79343162 + A/C rs28662236 79343365 + A/G rs34757274 79343581 + —/C rs654628 79343805 − C/T rs11755496 79343990 + C/G rs528850 79344165 + C/G rs16890160 79344345 + C/T rs1033691 79344906 + C/T rs1964131 79345300 + —/A/G rs1964132 79345301 + A/G rs627292 79345308 − A/G rs627289 79345314 − C/G rs7767332 79345618 + A/T rs9448480 79345810 + C/T rs605822 79345825 + A/G rs605697 79345910 + A/G rs605264 79346003 + C/T rs603964 79346271 − A/G rs612489 79346309 − G/T rs484582 79346824 + G/T rs35610422 79346949 + —/G rs35763342 79347019 + —/T rs9448481 79347164 + C/G rs9448482 79347421 + C/T rs597283 79347449 − C/G rs596810 79347562 − C/T rs596337 79347676 − C/T rs34739094 79347711 + —/G rs9448484 79347965 + C/T rs655566 79348564 − A/G rs581416 79348610 − C/G rs689389 79348661 − A/G rs846453 79348794 − C/G rs846452 79348887 − A/G rs11755342 79349385 + C/T rs34223893 79349579 + —/G rs674105 79349688 − A/G rs9448485 79350112 + A/G rs9443596 79350335 + A/G rs12181074 79350315 + A/G rs17225876 79350594 + C/T rs11751885 79350686 + A/G rs7746355 79351241 + A/C rs7746614 79351279 + C/T rs34541692 79351399 + —/A rs699174 79351582 − A/G rs9448486 79351645 + A/C rs699175 79351931 − C/T rs699176 79352012 − A/G rs236863 79352234 − A/G rs12207987 79352301 + G/T rs13201882 79352366 + A/G rs9448487 79352398 + G/T rs9443597 79352413 + C/T rs9448488 79352736 + C/T rs9443598 79352745 + C/T rs9448489 79352746 + A/G rs3967379 79353019 + C/T rs236864 79353190 + C/G rs12209919 79353401 + A/G rs12209974 79353466 + C/G rs236865 79353475 + C/G rs9443599 79354012 + A/G rs236866 79354277 − A/G rs1137258 79354328 + A/G rs9448490 79354814 + A/C rs17332393 79355181 + C/T rs11759337 79355380 + A/G rs236867 79355383 + C/T rs9448491 79355466 + A/G rs236868 79355488 + G/T rs236869 79355706 + C/T rs9443600 79356397 + G/T rs236870 79356774 + C/T rs236871 79356925 + C/T rs16890184 79357098 + C/T rs9443601 79357369 + A/G rs9448492 79357532 + C/T rs236872 79358008 − C/T rs9448493 79358214 + C/T rs7776020 79358245 + C/T rs236873 79358580 − A/G rs11753657 79358850 + A/C rs34736990 79359228 + —/T rs11461852 79359513 + —/T rs9448495 79359564 + C/T rs9448496 79359649 + A/G rs9448497 79360057 + C/T rs236874 79360347 + A/G rs9443602 79360653 + C/T rs192101 79360986 + A/G rs35198424 79361056 + —/A rs236875 79361403 + A/C rs11366261 79361558 + —/A rs236876 79362007 + C/G rs12203300 79362176 + A/T rs236877 79362203 + A/G rs9448498 79362482 + A/G rs11756326 79362950 + A/G rs9448499 79363791 + A/C rs9448500 79363928 + A/T rs10485131 79364083 − C/T rs7770444 79364354 + C/T rs11757555 79364553 + A/C rs236878 79364707 − G/T rs910955 79364822 + A/G rs70478 79364899 + C/T rs70480 79365324 + A/G rs5877620 79365398 + —/T rs731449 79365401 − A/G/T rs35967646 79365405 + —/A rs9294120 79365528 + C/T rs35822945 79365869 + —/T rs9343779 79365908 + A/G rs699178 79366002 + C/T rs2750022 79366008 + A/C rs699179 79366252 + A/G rs699180 79366351 + C/T rs9448502 79366447 + A/C rs35286686 79366524 + —/T rs9448503 79366694 + C/G rs35383112 79367223 + —/A rs699181 79367333 + C/T rs7356833 79367828 + A/G rs7356834 79367837 + A/G rs34785800 79367950 + —/T rs7356836 79367968 + A/G rs5877621 79368047 + —/C rs7356840 79368100 + A/G rs7356843 79368150 + G/T rs9294121 79368152 + G/T rs7356844 79368157 + A/G rs236879 79368578 − A/C rs34335044 79368627 + —/C rs9448504 79369400 + C/G rs9448505 79369555 + C/T rs9448506 79369591 + A/T rs9359332 79369685 + G/T rs236880 79369811 − A/T rs9448507 79370086 + A/G rs9448508 79370320 + A/G rs9443603 79370631 + A/C rs236881 79370661 − C/G rs9448509 79371433 + A/G rs11964133 79371604 + C/T rs35268570 79371715 + —/G rs498037 79371989 − A/G rs1570075 79372076 + A/C rs1567097 79372765 − A/T rs1567096 79372799 − A/G rs236882 79372832 + A/G rs12200556 79372896 + C/T rs10806133 79372949 + C/T rs35217057 79373409 + —/TGGA rs717364 79374159 + A/G rs11757996 79374370 + C/T rs1995650 79375007 − C/T rs500391 79375065 + A/G rs596057 79375070 − A/C rs34948829 79375296 + G/T rs2021855 79375397 − A/T rs17226851 79375471 + A/G rs984157 79375681 − C/T rs1395447 79376010 − C/T rs9361411 79376022 + A/G rs236883 79376130 − A/C rs236884 79376244 + C/G rs9448510 79376314 + C/T rs12197910 79376609 + C/T rs2307943 79376998 + —/AA rs10539915 79376999 + —/AA rs4551135 79377021 + G/T rs10943547 79378077 + A/G rs236885 79378204 + A/G rs236886 79378253 + A/C rs10943548 79378357 + C/T rs35488554 79378364 + A/C rs236887 79378393 − A/T rs16890218 79378495 + G/T rs236888 79378960 + C/T rs236889 79379130 − A/G rs16890224 79379278 + A/T rs1407102 79379719 + C/T rs17825291 79379916 + C/T rs34286917 79380641 + —/A rs1012026 79381031 + A/G rs236890 79381351 + A/C rs236891 79381414 + C/T rs1012027 79381592 + C/T rs34331673 79382209 + —/G rs9448511 79382811 + C/T rs17227220 79382837 + A/G rs16890230 79382886 + A/T rs236892 79382966 − C/T rs12189761 79382972 + A/T rs12209692 79383101 + A/G rs1395446 79383114 − A/C rs34707756 79383315 + —/A rs16890234 79383336 + A/G rs2021251 79383492 − C/G rs10943549 79383908 + C/T rs699182 79384047 + G/T rs3035341 79384211 + —/AAAAA rs34681522 79384257 + —/T rs1186428 79384269 − A/G rs2022521 79384282 − G/T rs817889 79384562 − A/G rs6931841 79384660 + C/T rs6932494 79384868 + A/G rs9359333 79384897 + C/T rs12213548 79385071 + G/T rs12525083 79385670 + G/T rs11970272 79385707 + C/T rs10455349 79387663 + C/G rs2063045 79388058 − A/G rs11757737 79388316 + A/C rs12197137 79388567 + A/G rs9448512 79389055 + A/T rs35065237 79389616 + —/T rs10630134 79389747 + —/TA rs34896371 79389748 + —/TA rs34598417 79389756 + —/AT rs236859 79389835 − C/T rs6454064 79389958 + G/T rs6454065 79390047 + G/T rs41501448 79390057 + C/T rs10640580 79390177 + —/CACA rs34677786 79390178 + —/CACA rs10565820 79390187 + —/CA rs10542873 79390189 + —/CA rs10536481 79390190 + —/AC rs6454066 79390202 + C/T rs6454067 79390311 + C/T rs1567095 79390707 − C/T rs1570001 79390750 + C/T rs236860 79390814 − C/T rs236861 79390866 + C/T rs12530012 79390899 + C/T rs9443604 79391001 + C/G rs12530067 79391157 + C/T rs12530068 79391178 + C/T rs12530072 79391243 + C/T rs4286729 79391508 + C/T rs236862 79391691 − A/G rs35710435 79391916 + —/G rs5877622 79391938 + —/G rs12190115 79392540 + A/G rs699183 79392730 + A/G rs34692849 79392774 + —/T rs10943550 79392824 + G/T rs10943551 79393059 + G/T rs11413951 79393172 + —/A rs35198419 79393180 + —/A rs35839290 79393308 + C/T rs11752300 79393726 + C/T rs12200526 79393754 + C/T rs12193597 79393898 + A/G rs12524686 79394235 + C/G rs35481326 79394369 + —/C rs659108 79395159 − G/T rs7775572 79395255 + C/T rs7755578 79395265 + A/G rs12195709 79395315 + A/G rs7775782 79395445 + C/T rs7755682 79395539 + C/T rs12210711 79396008 + A/G rs236853 79396185 − A/G rs34570358 79396388 + —/T rs35919105 79396567 + C/T rs12530353 79396617 + A/G rs6940529 79396666 + A/C rs12530368 79396668 + A/G rs6940555 79396714 + A/C rs6941006 79396789 + A/G rs6920658 79396993 + C/T rs11755479 79397125 + A/T rs12665819 79397185 + A/G rs9448513 79397377 + A/G rs12191138 79397842 + C/G rs10615883 79397992 + —/TC rs10563095 79397998 + —/TC rs236854 79398400 + G/T rs236855 79398610 − A/G rs9443605 79398716 + C/T rs497885 79398799 + G/T rs2321764 79399237 + C/G rs5018093 79399607 + C/T rs12201840 79399748 + C/T rs9448514 79399769 + A/C rs34938165 79400028 + —/GA rs35821097 79400053 + —/C rs7774339 79400463 + C/T rs236856 79400485 + A/G rs236857 79401130 + C/T rs9448515 79401281 + A/G rs236858 79401284 + C/T rs699184 79401788 − A/C rs512778 79401865 + A/G rs9361413 79401968 + A/G rs3220157 79402127 + (CA)24/25/ 26/28/29/30/ 31/33 rs36212818 79402095 + —/ CACACA CACA rs5877623 79402087 + —/ CACACA CACA rs33979908 79402121 + —/ CACACA CACACA rs9361414 79402167 + G/T rs5877624 79402681 + —/G rs541337 79402708 + A/G rs2321765 79402846 + C/G rs699185 79403177 + A/G rs236848 79403803 + A/G rs11965655 79403862 + A/G rs236849 79403916 − A/G rs10701196 79403945 + —/AA rs35128239 79404539 + —/C rs236850 79405375 + A/C rs6904390 79405458 + A/T rs6909051 79405613 + C/T rs12206138 79405708 + C/T rs34566789 79405761 + —/C rs6909339 79405768 + C/G rs6909644 79405797 + A/G rs6909663 79405829 + G/T rs6910018 79405963 + A/G rs171050 79406031 + A/G rs236851 79406471 + A/G rs236852 79406611 + A/C rs35683036 79406788 + —/C rs7763429 79407488 + A/G rs28797508 79407906 + A/T rs34457432 79407905 + —/A rs28845244 79407909 + A/T rs11967330 79408002 + G/T rs9766611 79408248 + C/G rs9767153 79408285 + C/T rs11967401 79408313 + G/T rs34710160 79408331 + —/T rs9767594 79408340 + A/G rs9767160 79408362 + C/T rs9766716 79408582 + C/T rs9766717 79408597 + C/T rs9767724 79408721 + A/G rs9767248 79408857 + C/T rs11755206 79408909 + C/T rs11755256 79408948 + G/T rs663954 79408987 + C/G rs35768463 79409014 + C/G rs2202590 79409231 − A/C rs34750624 79409440 + —/AACA rs12527236 79409757 + C/G rs7740665 79410184 + C/T rs4547970 79410315 + A/G rs34273395 79410347 + —/T rs10455350 79410646 + A/G rs583747 79411314 − A/T rs10455351 79411324 + G/T rs34113682 79411805 + —/C rs6936649 79411878 + A/T rs6913931 79412046 + C/T rs9343780 79412054 + C/T rs1172263 79412098 − A/T rs7751786 79412433 + A/T rs1069028 79412764 − A/C rs4706716 79412775 + G/T rs7738229 79412794 + A/T rs7756398 79412809 + A/C rs7756411 79412884 + A/C rs7756809 79412901 + A/G rs7756442 79412946 + A/G rs34345701 79412986 + G/T rs9448517 79413089 + G/T rs11753268 79413379 + A/G rs2202589 79413464 − A/G rs2202588 79413475 − C/T rs11758439 79413558 + C/T rs7761199 79413617 + A/G rs11753781 79413684 + A/C rs10455119 79413685 + A/G rs34530796 79414858 + —/T rs9448518 79414973 + A/G rs9443606 79415015 + C/G rs9443607 79415153 + C/T rs13213955 79415197 + A/T rs9350767 79415702 + A/C rs7772851 79416038 + C/T rs6454070 79416268 + A/C rs7773660 79416279 + A/G rs7773550 79416449 + A/G rs9448519 79416456 + C/G rs7773732 79416491 + A/C rs9448520 79416508 + A/G rs9361418 79416542 + C/T rs7774017 79416543 + A/G rs34978259 79416789 + —/C rs13199250 79416845 + A/C rs12528155 79417363 + A/G rs12528140 79417430 + A/C rs12524711 79417477 + A/G rs12528168 79417483 + A/G rs12529963 79417494 + A/T rs12525058 79417555 + A/T rs12528513 79417619 + C/G rs35973698 79417626 + —/A rs9448521 79418135 + C/T rs13204264 79418289 + A/C rs13204489 79418306 + G/T rs13220434 79418337 + C/T rs13204504 79418338 + A/G rs13204411 79418403 + A/C rs10943555 79418521 + A/G rs12182690 79418612 + C/T rs11758282 79418731 + A/G rs10943556 79418749 + A/C rs11758301 79418757 + G/T rs12182714 79418795 + A/C rs10943557 79418878 + C/T rs10943558 79418957 + A/G rs10943559 79418973 + A/C rs12529060 79419023 + G/T rs12529083 79419172 + A/G rs12529066 79419210 + C/T rs13208861 79419298 + C/G rs35723058 79419309 + —/T rs12524083 79419353 + C/T rs4481395 79420009 + A/G rs9359334 79420248 + C/G rs12662183 79420296 + A/G rs13202661 79421089 + G/T rs2321767 79421453 + C/T rs6921541 79421621 + C/T rs11750986 79422024 + C/T rs11755647 79422090 + A/C rs35959932 79422201 + —/C rs34291901 79422318 + A/T rs9343782 79422366 + G/T rs34044761 79424096 + —/G rs11399404 79424247 + —/A rs17234476 79425078 + G/T rs5877625 79425313 + —/T rs35681689 79425314 + —/T rs34020492 79425316 + —/T rs13220214 79425378 + G/T rs12210702 79426052 + A/G rs12525652 79426301 + A/C rs1938554 79426313 + C/G rs12525655 79426333 + C/T rs35676724 79426360 + —/T rs12525674 79426408 + C/T rs12527490 79426534 + A/T rs36020193 79426610 + —/T rs12530352 79426691 + A/G rs12526918 79426820 + A/G rs12215953 79426831 + C/T rs2154396 79426988 + C/T rs10943560 79427137 + C/T rs35902159 79427208 + —/AAT rs6941828 79427531 + C/G rs17234622 79427610 + A/G rs10485130 79427659 − A/G rs10485129 79427902 − C/T rs17826325 79427930 + C/T rs10485128 79428165 − A/C rs9361420 79428649 + A/G rs17826379 79428843 + A/C rs9443608 79429038 + A/T rs7768733 79429515 + C/T rs12194701 79429556 + A/G rs12528303 79429558 + A/C rs7752431 79429626 + C/T rs12524924 79429653 + C/T rs12524949 79429719 + A/G rs1938555 79430010 + A/G rs1938556 79430133 + A/G rs11962962 79430380 + C/G rs35016983 79430502 + —/T rs12661567 79430711 + C/T rs9448524 79430774 + C/G rs12196899 79431241 + A/G rs7453195 79431988 + G/T rs35095504 79432065 + C/T rs11756592 79432239 + C/T rs12198749 79432255 + C/T rs11754162 79432324 + A/G rs11964250 79432345 + C/T rs11756635 79432372 + C/T rs12198976 79432495 + C/G rs11758823 79432516 + A/G rs12526451 79432811 + A/G rs35824053 79432979 + —/GT rs9361422 79434457 + C/G rs12527341 79434703 + C/T rs34470324 79434880 + —/T rs16890254 79435141 + G/T rs11751443 79435191 + A/G rs10943561 79435271 + A/G rs34358078 79435272 + AT/GC rs10943562 79435272 + C/T rs11758593 79435318 + G/T rs11759124 79435551 + A/T rs17234902 79435793 + A/G rs1954659 79436179 − G/T rs9443609 79436197 + A/C rs1954658 79436315 − G/T rs11756825 79436318 + A/G rs1954657 79436419 − A/G rs34627531 79436474 + A/G rs17826615 79436664 + C/T rs17235062 79436828 + C/G rs9359335 79436942 + C/T rs16890261 79437480 + A/G rs34327517 79437516 + —/C rs17235125 79437555 + A/G rs17235167 79437614 + C/G rs17235209 79437636 + C/T rs34645505 79437645 + —/C rs17826801 79437741 + A/G rs16890263 79438616 + C/T rs2321768 79438791 + A/T rs12201253 79439572 + G/T rs34671943 79439692 + —/C rs6914850 79439950 + C/G rs12194506 79440009 + A/G rs1938553 79440281 − A/C rs1938552 79442027 − C/G rs1938551 79442188 − A/G rs1938550 79442759 − G/T rs1938549 79442785 − C/G rs4371819 79443838 + A/G rs3207577 79443876 + G/T rs2226283 79444234 − C/T rs34263174 79444643 + —/C rs9443610 79444913 + C/T rs6901727 79444923 + A/G rs9359337 79446035 + C/T rs9352610 79446117 + A/G rs4590226 79446611 + C/G rs4568410 79448079 + A/G rs4358581 79448365 + A/G rs36159891 79448536 + —/G rs12214797 79448885 + A/G rs12203087 79449566 + C/T rs1938548 79450052 + A/G rs237114 79450160 + C/G rs237113 79450255 + C/T rs9448526 79450659 + A/G rs9294124 79450941 + C/T rs237112 79451719 + A/G rs9443611 79451898 + C/T rs28510272 79452108 + G/T rs5877626 79452148 + —/T rs28715651 79452155 + C/T rs36084918 79452165 + —/T rs237111 79452657 + A/C rs9359338 79453470 + C/T rs9352611 79453687 + C/T rs9448528 79453785 + C/T rs190210 79455101 − A/G rs633117 79456053 + C/T rs36071262 79456190 + —/T rs578709 79456303 + C/T rs9448529 79456446 + A/G rs631308 79456494 + C/T rs580694 79456568 + C/G rs496269 79457094 − A/G rs10678940 79457699 + —/AATG rs35912544 79457700 + —/AATG rs35640072 79457977 + —/C rs639370 79458132 + C/T rs2307947 79458723 + —/AAG rs1180811 79458783 + A/G rs10943567 79459170 + C/T rs500306 79459437 + C/T rs621121 79459440 − A/G rs524008 79459763 + A/C rs605868 79460512 + A/C rs553313 79460609 + A/G rs605016 79460685 − C/G rs553545 79460686 + A/C rs10943568 79460926 + G/T rs557062 79461079 + C/T rs9359339 79461851 + A/G rs1099816 79461906 + A/G rs1099817 79462027 + A/C rs11760142 79462156 + A/G rs36155678 79462155 + —/A rs237117 79462475 − C/T rs34503722 79462774 + —/T rs36003173 79463000 + CAT/TGG rs9352612 79463306 + C/T rs35073587 79463953 + —/T rs237116 79465318 − A/G rs13219002 79465340 + G/T rs36187425 79465396 + —/T rs4116296 79465874 + A/C rs9688758 79465988 + C/T rs36167084 79466143 + —/A rs11759842 79466549 + G/T rs237115 79467111 + A/G rs11751263 79467773 + C/T rs10591157 79468622 + —/AGG rs1180810 79468743 + C/G rs12192387 79468754 + C/T rs9361423 79468991 + G/T rs13197296 79469397 + A/C rs13197299 79469399 + A/C rs13197312 79469415 + A/T rs13197402 79469451 + A/C rs13197429 79469504 + A/C rs13197432 79469507 + A/C rs237110 79469629 − C/G rs35083334 79470193 + —/T rs34384472 79470458 + —/C rs35723904 79470956 + —/T rs237109 79471413 − A/T rs9343786 79471447 + A/C rs34396685 79471699 + —/G rs237108 79471734 + C/T rs28526821 79472111 + A/G rs9343787 79472325 + A/C rs9343788 79472577 + A/G rs237107 79472599 + A/G rs11337252 79472738 + —/A rs11322370 79472755 + —/A rs9448533 79473558 + A/G rs4706718 79473602 + A/G rs7773448 79474075 + C/T rs12662772 79474252 + C/G rs34988548 79474267 + —/T rs34521774 79474321 + —/A rs16890280 79474935 + C/T rs1180809 79474961 + A/G rs35874347 79475533 + —/C rs9341739 79475795 + C/G rs10485127 79476149 − C/T rs1782783 79476375 − A/G rs34305826 79476572 + —/C rs11758421 79477277 + A/G rs1180829 79477495 − A/G rs17642139 79477518 + C/T rs11380286 79477603 + —/G rs7748153 79477872 + C/T rs9341740 79479508 + G/T rs34794581 79480689 + —/G rs10613222 79480812 + —/ ATATAT ATAT rs10613221 79480824 + —/AT rs35653902 79480973 + —/G rs9352613 79481152 + A/G rs11363389 79481250 + —/A rs10589550 79481315 + —/ ATATAT AT rs34184424 79481323 + —/ATAT rs1180812 79481799 + G/T rs1180813 79482210 + C/T rs1180814 79482234 + A/G rs10455352 79482310 + A/G rs1180815 79482567 + C/T rs1185719 79483043 + A/G rs1180816 79483108 + A/C rs9343789 79483300 + A/G rs9341741 79483557 + A/G rs35281441 79483695 + A/C rs1180817 79483705 + A/G rs6923778 79483808 + A/G rs1180818 79483938 + C/G rs35304238 79484265 + —/A rs28702778 79484289 + A/C rs28667093 79484464 + A/G rs12197635 79484466 + A/G rs11403769 79484690 + —/A rs33917829 79484698 + —/A rs35564110 79484699 + —/A rs1180819 79484743 + A/G rs1180820 79485455 + A/G rs1543481 79485804 + C/G rs1543482 79485857 + A/G rs1543483 79485890 + A/T rs1180821 79486391 + A/G rs9448534 79486474 + C/T rs28831831 79486721 + C/T rs2224461 79487062 + A/G rs2208518 79487184 + G/T rs13198615 79487271 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rs7382016 79512500 + A/T rs7382311 79512662 + A/G rs7383685 79512701 + C/T rs35420186 79512878 + —/CAA rs9448549 79512991 + A/G rs9350771 79513107 + C/T rs9350772 79513288 + A/C rs9350773 79513424 + A/C rs9359343 79513450 + A/G rs2145686 79513681 + A/C rs7759829 79513725 + C/G rs7759687 79513734 + A/G rs7760429 79513941 + A/G rs7760193 79514040 + A/C rs9352628 79514166 + G/T rs9361426 79514269 + A/C rs9448551 79514294 + C/T rs1998252 79514720 + C/T rs10943576 79514771 + G/T rs34981854 79514975 + —/G rs34769649 79515326 + —/T rs7766517 79515467 + C/T rs7766791 79515472 + A/G rs10559249 79515694 + —/GTGT rs5877628 79515693 + —/TG rs3035376 79515718 + —/GT rs1319575 79515770 + C/T rs3918524 79515816 + A/G rs1158575 79515925 + C/T rs4706066 79516496 + C/T rs2145687 79516920 + C/T rs2145688 79516936 + C/T rs34523548 79517003 + —/T rs35884007 79517112 + —/G rs35363076 79517166 + —/G rs961680 79517338 + A/T rs9359344 79517752 + A/G rs4141594 79517914 + A/C rs9443614 79517919 + A/G rs9350774 79518322 + A/G rs9294125 79518365 + A/T rs35542025 79518386 + —/A rs12528472 79518434 + C/G rs1475046 79518520 + A/G rs9294126 79518524 + A/C rs9352629 79518599 + A/T rs10943577 79518602 + C/G rs9343800 79518691 + A/G rs9352630 79518911 + C/T rs9352631 79518916 + A/G rs9352632 79518945 + C/G rs9343801 79518994 + A/G rs12196839 79519152 + A/G rs9352633 79519342 + C/G rs9352634 79519344 + A/G rs4706722 79519416 + C/T rs4706723 79519455 + C/G rs35622574 79519529 + —/C rs4706724 79519540 + A/G rs9448553 79520364 + G/T rs9350775 79520504 + A/G rs9350776 79520564 + A/G rs4590227 79520629 + A/G rs7451373 79520890 + C/T rs9350777 79520900 + A/C rs9361427 79521580 + A/T rs2321771 79522159 + C/T rs6454077 79522624 + A/G rs4706725 79523110 + A/G rs4706726 79523256 + C/G rs4706727 79523430 + C/T rs4706728 79523530 + G/T rs4706729 79524311 + G/T rs4706730 79524622 + A/G rs35493328 79524755 + —/A rs9343804 79524771 + A/G rs9343805 79524845 + G/T rs4706731 79525017 + C/T rs6916201 79525202 + C/T rs4706732 79525233 + A/C rs4706733 79525331 + C/T rs4706734 79525369 + C/T rs4706067 79525544 + A/G rs4706735 79525556 + C/T rs4706068 79525824 + C/T rs7758474 79525893 + C/G rs7758382 79526025 + C/T rs7758411 79526113 + A/G rs7758668 79526149 + C/G rs7758709 79526220 + A/C rs9343809 79526430 + A/G rs9352638 79526528 + A/G rs9352639 79526557 + A/G rs9352640 79526632 + C/T rs9359345 79526635 + A/C rs9361430 79526795 + C/T rs9361431 79526796 + A/G rs12215488 79526895 + A/G rs4277969 79527116 + C/T rs9343810 79527190 + C/G rs9343811 79527285 + C/T rs36159791 79527300 + —/G rs6939408 79527324 + A/G rs9361432 79527332 + A/G rs9352641 79527639 + A/G rs9361433 79527970 + A/G rs9352642 79528071 + A/C rs4706069 79528287 + C/T rs11751339 79528440 + A/C rs4706070 79528478 + A/G rs36193003 79528479 + AA/GG rs4706071 79528479 + A/G rs9359346 79528869 + A/G rs7746103 79529063 + C/T rs9352645 79529280 + C/G rs7746449 79529347 + A/C rs9352646 79529377 + A/G rs4419638 79529395 + C/G rs36146147 79529439 + —/G rs9341748 79529663 + A/G rs9343814 79529792 + C/G rs9448558 79529987 + C/G rs10943581 79530174 + C/T rs28716526 79530437 + A/G rs11752708 79530459 + G/T rs11752686 79530498 + C/T rs6899455 79530697 + C/T rs34374962 79530898 + A/C rs9448559 79531201 + A/G rs6920807 79531450 + A/T rs2135769 79532044 + A/G rs4706736 79532195 + A/T rs4706072 79532210 + A/G rs1588086 79532606 + C/T rs1588087 79532636 + A/T rs2321772 79532909 + G/T rs9443616 79532925 + A/G rs2321773 79532962 + A/G rs2321774 79533169 + C/T rs9443617 79533254 + A/G rs34749198 79533559 + —/T rs1073211 79533575 − C/T rs28845538 79533674 + C/T rs2135770 79533747 + A/C rs9341750 79534203 + C/T rs6938951 79534339 + A/C rs6939263 79534367 + C/T rs9359348 79534401 + A/T rs6900794 79534563 + C/T rs34763883 79534693 + —/A rs6901015 79534742 + C/T rs6924048 79534918 + C/T rs36084053 79535093 + —/C rs10943583 79535183 + C/G rs35165607 79535238 + —/C rs34534036 79535250 + —/C rs11755934 79535340 + C/T rs2321775 79535509 + C/T rs9359350 79535870 + C/G rs9361437 79536054 + C/T rs9361438 79536280 + C/T rs9352648 79536460 + A/G rs9341751 79536555 + C/T rs9448560 79536601 + A/G rs9448561 79536715 + A/G rs9343820 79537177 + A/T rs11965322 79537414 + A/T rs36082173 79537823 + —/T rs6923812 79538338 + C/T rs9350781 79538534 + A/T rs1876389 79538651 + A/T rs35000167 79538888 + —/T rs11961822 79539174 + A/G rs35722542 79539754 + —/A rs12663824 79539849 + A/C rs1021987 79539884 + C/G rs1507151 79539965 + C/T rs1507152 79540193 + C/T rs1567169 79540652 + C/T rs1507153 79541105 + A/C rs35498910 79541112 + —/T rs9448562 79541799 + G/T rs1876390 79542282 + C/T rs9448563 79543216 + A/G rs9448564 79543231 + C/T rs9448565 79543237 + C/T rs16890304 79543377 + A/G rs1876391 79543470 + C/T rs6454082 79544001 + C/T rs4555886 79544101 + A/T rs34032635 79544308 + —/T rs34806029 79544385 + —/G rs11758151 79544940 + C/T rs11758164 79544958 + G/T rs6928279 79545677 + C/T rs9361440 79546395 + A/C rs9352649 79546502 + G/T rs34850892 79547499 + —/C rs9361441 79547685 + A/G rs35665788 79547866 + —/T rs35275890 79549004 + —/A rs35562053 79549016 + A/T rs6935486 79549211 + A/G rs9359351 79549252 + A/G rs11755568 79550337 + C/T rs34268443 79550347 + —/C rs6942344 79550522 + C/T rs2321893 79550527 + C/T rs9352650 79550613 + A/G rs11751437 79550636 + A/G rs9361442 79550764 + A/G rs6904016 79550772 + C/T rs4055608 79550977 + C/T rs9350782 79551187 + A/G rs9352652 79551451 + A/G rs10806148 79551623 + A/G rs34335705 79552378 + C/T rs12181706 79552458 + C/G rs9361443 79552769 + A/C rs2874642 79552903 + A/G rs12176501 79553029 + C/T rs9343822 79553040 + A/T rs7773850 79553042 + A/T rs7773851 79553044 + A/T rs11757519 79553160 + C/T rs35940795 79553244 + —/C rs35004706 79553408 + —/C rs9352653 79553582 + A/G rs9343823 79553825 + A/C rs9343824 79554288 + A/G rs35245361 79554378 + —/A/T rs1507155 79554584 + A/G rs2021541 79554588 + A/G rs13210672 79554590 + A/G rs9343826 79554632 + A/G rs1507156 79554776 + A/G rs34136836 79555385 + —/G rs34958301 79556015 + —/G rs9361444 79556792 + C/T rs1507149 79556805 − C/G rs9352654 79557000 + A/G rs9343827 79557755 + A/G rs9359352 79558729 + C/T rs7757382 79558996 + C/G rs10943585 79559128 + C/G rs9361445 79559275 + C/T rs5877629 79559295 + —/T rs1827992 79559524 − A/G rs7762022 79559578 + A/C rs6926463 79559890 + A/G rs6454083 79560137 + C/T rs9352655 79560142 + A/T rs1507154 79560419 + C/T rs1476304 79560439 + C/T rs1476305 79560605 + G/T rs4628052 79560919 + A/G rs13200035 79561004 + C/T rs13214259 79561046 + A/C rs13200136 79561064 + C/T rs13214670 79561072 + A/G rs13214372 79561084 + A/G rs13200153 79561107 + C/T rs13214383 79561121 + A/G rs28781665 79561419 + A/G rs1848194 79562087 + C/T rs35374025 79562246 + —/T rs1911513 79562355 + A/G rs9448568 79562434 + A/G rs7774691 79562517 + C/G rs9352657 79562804 + C/G rs7741245 79563215 + A/G rs7741407 79563307 + A/G rs7761613 79563435 + C/T rs35613790 79563516 + —/A rs6454084 79563604 + A/G rs4446522 79564225 + A/T rs6931419 79564240 + A/T rs4334937 79564258 + C/T rs12527806 79564386 + A/T rs3967330 79564533 + A/C rs9448572 79565438 + G/T rs10943587 79565451 + C/T rs9443619 79565631 + C/T rs7756996 79566086 + A/C rs11753266 79566107 + C/T rs1857957 79566184 − C/G rs28759673 79566270 + G/T rs2321896 79566463 + C/G rs41503746 79566463 − C/G rs35414898 79566540 + —/A rs34037147 79566911 + —/C rs10943588 79567713 + A/C rs11751036 79567797 + C/T rs2202662 79568057 − G/T rs2202661 79568299 − A/G rs2202660 79568463 − G/T rs9448573 79569097 + C/T rs6913028 79570309 + C/T rs6454085 79570611 + C/G rs4706737 79570764 + A/G rs35196425 79570832 + —/T rs4706075 79570837 + C/G rs4706076 79570871 + C/CA/T/TG rs4706738 79570872 + A/G rs2202659 79571328 − A/G rs12662944 79571375 + A/T rs9350784 79572125 + C/T rs9350785 79572304 + C/T rs9448574 79573020 + A/C rs9448575 79573525 + G/T rs1814219 79573704 − G/T rs13216900 79573706 + A/G rs34791687 79573717 + —/G rs9350786 79574025 + G/T rs35713298 79574030 + —/GGG rs13217367 79574256 + A/T rs9343834 79574390 + A/G rs12203336 79575034 + G/T rs35790661 79575375 + —/CA rs2202658 79576388 − C/T rs906320 79576561 − A/G rs41269335 79576661 + G/T rs34943334 79576824 + A/G rs906319 79577408 − C/T rs41269337 79577988 + A/G rs6454086 79578882 + C/T rs9361448 79579645 + G/T rs9352659 79580583 + A/G rs9448576 79580987 + C/G rs2202663 79581585 + C/T rs1395655 79581612 + C/T rs7773491 79582941 + C/T rs4640849 79583469 + A/G rs35044999 79584659 + —/C rs12524858 79586232 + G/T rs2202664 79586366 + C/G rs9448577 79586917 + C/G rs28814638 79587149 + A/G rs34428579 79587468 + —/A rs12209635 79588934 + C/T rs955765 79589329 − A/G rs5877630 79589377 + —/G rs9448578 79589928 + G/T rs4706739 79590001 + C/T rs12213359 79590746 + A/C rs10556588 79592115 + —/AGAA rs12195716 79592131 + C/T rs6902294 79593001 + G/T rs1567168 79593174 + A/C rs2174740 79593284 + A/G rs2135767 79593386 + C/T rs6454088 79594398 + C/T rs12194457 79595224 + A/G rs35356883 79595302 + —/G rs12194642 79595510 + A/G rs9343838 79595869 + A/G rs10639111 79596351 + —/GAGA rs34962848 79596352 + —/GAGA rs34665735 79596358 + —/AGAG rs35366557 79596414 + —/G rs16890324 79596828 + A/G rs13217987 79597357 + A/G rs1963638 79597835 + G/T rs2013420 79597934 + A/G rs16890325 79597947 + C/T rs9352662 79598210 + A/G rs28626679 79598705 + C/G rs35393092 79598862 + —/T rs16890326 79599251 + C/T rs34305313 79600125 + —/A rs33920803 79600126 + —/A rs12110531 79600198 + C/G rs6912683 79600211 + A/C rs16890328 79600713 + A/C rs7754715 79600777 + A/G rs34253750 79601120 + —/G rs13208855 79602240 + G/T rs16890330 79602923 + A/C rs1021986 79603853 + C/G rs35242601 79604056 + —/T rs13220688 79604565 + C/T rs16890331 79605080 + C/T rs1507150 79605316 + A/T rs4706077 79605564 + A/G rs10806150 79605891 + A/G rs12664947 79606191 + A/T rs1542977 79607026 + G/T rs35949145 79607341 + —/A rs2174741 79607599 + A/C rs34567509 79608189 + —/C rs9448579 79608431 + C/T rs9448580 79608531 + C/G rs1027813 79608837 − A/C rs35909912 79609084 + C/T rs34385822 79609087 + C/T rs35544399 79609089 + C/T rs34033174 79609112 + C/T rs5877631 79609384 + —/T rs35937908 79609385 + —/T rs34696113 79609390 + —/T rs33954612 79609391 + —/T rs12664403 79610047 + G/T rs2135766 79610075 − A/G rs9448581 79610097 + A/G rs35179848 79610136 + A/C rs11332279 79610357 + —/A rs1567167 79610546 − A/G rs4415132 79610826 + C/T rs6926537 79610912 + A/T rs17741785 79610991 + A/G rs1507148 79611110 − C/T rs4409146 79611326 + C/T rs34490997 79611333 + —/G rs9361451 79611774 + C/T rs16890334 79612885 + C/T rs12196485 79613590 + A/G rs4147183 79613765 + C/G rs36024489 79614221 + G/T rs9352663 79614883 + C/T rs35934464 79615331 + —/C rs971994 79616321 − C/G rs7454053 79616439 + A/G rs10223389 79616629 + A/G rs12214796 79617787 + C/T rs17798356 79618153 + A/G rs12190108 79619374 + C/T rs4421161 79620938 + A/G rs12213652 79621099 + A/G rs2321894 79621148 + A/G rs9448583 79621405 + A/G rs9361454 79621963 + —/G/T rs12176511 79622440 + A/G rs34132605 79622874 + —/G rs9352664 79622881 + G/T rs10455354 79622949 + A/G rs2874643 79623036 + A/G rs1960542 79623362 + C/T rs9352665 79624438 + C/G rs9361455 79624601 + A/G rs34916187 79624764 + —/G rs12661039 79625256 + C/T rs4682456 79625580 − C/T rs7449459 79625728 + C/T rs6936109 79626595 + A/G rs12201183 79626839 + A/G rs6937465 79627064 + G/T rs9361458 79627515 + C/T rs11381253 79627547 + —/A rs34502239 79627557 + —/A rs9765849 79627608 + A/G rs9352666 79628903 + C/G rs9352667 79629015 + C/T rs9352668 79629397 + A/G rs9448584 79629518 + G/T rs9448585 79629560 + A/G rs9361459 79629641 + A/G rs9343841 79630723 + C/G rs6923327 79631594 + A/G rs10943595 79632010 + C/G rs34199187 79632011 + CC/GT rs10943596 79632011 + C/T rs34658311 79632386 + A/T rs11444087 79632386 + —/T rs7760883 79632388 + —/A/T rs35635397 79632389 + —/A rs16890347 79632927 + C/T rs9443621 79633218 + A/G rs41269339 79634131 + C/G rs9350789 79634363 + A/C rs9341753 79634515 + C/T rs12153837 79635921 + A/C rs12527589 79636178 + C/T rs10455355 79636221 + C/T rs34431699 79637008 + —/C rs6941317 79637771 + A/C rs7738062 79638242 + C/G rs4706740 79639381 + A/C rs34204884 79639456 + C/T rs9443622 79639509 + C/T rs4706078 79639525 + C/T rs35373380 79639573 + C/T rs12193104 79639633 + A/G rs12660767 79639652 + C/T rs35962544 79639717 + —/AA rs12193319 79640156 + A/C rs6454089 79640821 + C/T rs9352669 79640860 + G/T rs9352670 79641152 + A/G rs9341754 79641692 + A/C rs34538995 79641946 + —/GAAA rs9448586 79642219 + A/G rs34409101 79642323 + —/T rs9343843 79642344 + C/T rs35304712 79643086 + C/T rs9343844 79643182 + A/T rs9350792 79643892 + A/G rs35439908 79645611 + —/G rs9448587 79645751 + A/G rs9341755 79645767 + C/G rs9361460 79646186 + C/G rs9448588 79646780 + G/T rs9359354 79647104 + A/G rs35560175 79647373 + —/A rs34453824 79647874 + —/C rs2174743 79648524 − C/T rs2135772 79648767 − A/C rs1021988 79649380 − A/G rs35897423 79650428 + —/C rs9352671 79651798 + A/C rs6908105 79651816 + A/G rs4055605 79651890 + —/TCTTA rs35817888 79651891 + —/TCTTA rs35754813 79652867 + —/A rs2321895 79654080 + C/T rs35355117 79654223 + —/C rs9352672 79654253 + C/T rs34228023 79654468 + —/A rs35503114 79654971 + —/T rs34717008 79655526 + C/T rs36108843 79655546 + —/C rs34900932 79655547 + —/T rs34933654 79655550 + C/T rs34963207 79656023 + —/A rs9361462 79656183 + A/G rs35606311 79656863 + —/A rs12192086 79657229 + A/G rs9448589 79657767 + G/T rs9352673 79659462 + G/T rs9359355 79659533 + A/G rs9343845 79659752 + A/G rs36114710 79659754 + A/G rs9352674 79660060 + G/T rs35774009 79662784 + —/A rs36087293 79663083 + —/G rs9448590 79663148 + C/G rs9448591 79663209 + C/T rs36004777 79663275 + —/A rs4327648 79663334 + C/T rs10525714 79664847 + —/ ATATAT ATATATA TATATAT AT rs35395481 79664848 + —/ ATATAT ATATATA TATATAT AT rs34482864 79664856 + —/AT rs10700674 79664871 + —/AT rs7776322 79666464 + A/T rs2174742 79666820 + G/T rs2135771 79667075 + C/T rs6941107 79667642 + A/G rs10943600 79668224 + A/G rs9343846 79668848 + A/T rs35533616 79669465 + —/A rs9352675 79669519 + A/G rs1354831 79670295 + C/T rs1354832 79670482 + C/T rs35112046 79671111 + —/C rs9443623 79671372 + C/T rs4706079 79671927 + A/G rs4706742 79672269 + C/T rs4706743 79672512 + G/T rs2174744 79673008 + A/T rs9448592 79673037 + C/G rs35935416 79673657 + —/T rs6915030 79674241 + C/T rs9361466 79675071 + C/T rs10806151 79676098 + C/T rs11402304 79676284 + —/T rs7756858 79676687 + A/G rs9443624 79676995 + A/G rs6921318 79677095 + A/G rs7758407 79677426 + C/G rs34373655 79677787 + —/T rs9361467 79677817 + A/G rs9343848 79677820 + C/T rs9361468 79677933 + A/G rs9448594 79679933 + A/T rs9448595 79680349 + A/G rs1963080 79681257 + A/G rs5877633 79681440 + —/G rs35590303 79682202 + —/C rs2063124 79683041 + C/T rs7756648 79683805 + A/T rs35313944 79684092 + —/A rs9343849 79684179 + A/G rs12196457 79684462 + A/T rs7767182 79685667 + A/C rs35777909 79685724 + —/G rs36012949 79685747 + —/C rs9448596 79686148 + C/T rs9443626 79686283 + C/G rs9352676 79686718 + A/G rs7750836 79688302 + C/G rs9350794 79688561 + C/T rs7755754 79689008 + A/G rs36181347 79689691 + —/A rs7760866 79689848 + C/G rs9361472 79690160 + G/T rs36132801 79690225 + —/G rs9448597 79690306 + C/T rs9689724 79690631 + A/G rs9343851 79690827 + C/G rs34433262 79690888 + —/C rs9688928 79691098 + A/C rs28826982 79691188 + A/G rs34236947 79691189 + AC/GG rs28811946 79691189 + C/G rs9359358 79692407 + C/T rs2089416 79692807 + G/T rs34521933 79693343 + —/C rs2135768 79693482 + C/T rs7744604 79694234 + A/C rs10755377 79694644 + C/T rs5877634 79696377 + —/T rs11430514 79697407 + —/T rs35387172 79697408 + —/T rs9350795 79697410 + A/T rs12665761 79697747 + C/T rs13205569 79697785 + G/T rs2321897 79698887 + C/T rs1911512 79699043 + C/T rs9343853 79699300 + C/T rs12660760 79699828 + C/T rs12660770 79699923 + C/T rs35416532 79700122 + —/TTT rs9343854 79700770 + A/C rs1044313 79702339 − A/T rs35580162 79703022 + —/C rs35881759 79703274 + —/C rs35125759 79703290 + —/C rs1044309 79703294 − C/T rs34261531 79703338 + —/C rs5877635 79704127 + —/T rs35000895 79704129 + —/T rs4464748 79704697 + C/G rs10654924 79706512 + —/AA rs34701016 79706513 + —/AA rs13191571 79706985 + G/T rs36155238 79706984 + —/T rs36160851 79706985 + —/T rs36170973 79706986 + —/T rs36132527 79707051 + —/G rs11547229 79707066 + A/G rs6900790 79707081 + C/T rs34609668 79707212 + G/T rs2485701 79707264 + A/G rs1876387 79707310 + A/G rs1876388 79707370 + G/T rs34463462 79707429 + G/T rs10574664 79707958 + —/AC rs28606484 79709319 + C/T rs9350796 79710116 + C/T rs6454090 79710425 + —/ A/AA/AA A/T/TT rs6454091 79710426 + A/T rs35306286 79710425 + —/AAA rs11370303 79710434 + —/A rs11432700 79710436 + —/A rs11447037 79710449 + —/A rs9443629 79710479 + A/C rs34717491 79710843 + —/C rs7740307 79710873 + A/T rs9688399 79711374 + A/G rs5877636 79711409 + —/A rs33977407 79711410 + —/A rs10943605 79712196 + A/G rs1135076 79712453 − A/G rs1056960 79712497 − C/T rs34050775 79713035 + —/A rs36048894 79713183 − A/C rs1056959 79713195 − A/G rs1056958 79713223 − C/T rs2275291 79713281 − A/T rs2275290 79713289 − C/T rs9361473 79713761 + C/T rs1984195 79714110 − C/T rs11370597 79714395 + —/C rs1283320 79714834 + C/G rs35766012 79714947 + —/T rs35205946 79715066 + —/G rs4706745 79715247 + C/T rs2063123 79715254 + C/T rs12529691 79715751 + A/G rs2174739 79715889 + A/G rs9343855 79716132 + G/T rs34526870 79716648 + —/C rs35018864 79717062 + —/C rs2050661 79717844 − A/G rs28623652 79718361 + C/T rs9443630 79718517 + G/T rs10943606 79718496 + G/T rs9448600 79719788 + A/C rs9443631 79720837 + C/T rs9443632 79721159 + C/T rs10455356 79721467 + C/T rs7753358 79721929 + A/T rs11316583 79723594 + —/T rs5877637 79724015 + —/A rs35159735 79724505 + —/C rs34936739 79725919 + —/C rs35865427 79726072 + —/C rs12665739 79727563 + C/T rs6940635 79727692 + C/T rs946022 79728852 + G/T rs3805746 79729157 + C/T rs3805747 79729241 + A/G rs34841569 79729665 − A/C rs4706746 79730895 + A/G rs13202531 79730981 + C/T rs35504170 79731083 + —/C rs10943608 79731648 + C/T rs3834844 79731991 + —/CTT rs3763160 79731994 + A/G rs9350797 79732420 + A/G rs11964204 79732781 + A/G rs10943609 79733047 + A/T rs1572586 79733060 + C/T rs1538234 79733298 + C/T rs3834845 79733766 + —/C rs34920411 79734822 + —/C rs9343856 79734930 + A/G rs10531246 79735174 + —/TAAT rs34584316 79736188 + —/T rs12663267 79736218 + C/G rs7742746 79736246 + G/T rs7742874 79736287 + A/G rs7742431 79736296 + A/G rs34480532 79736437 + —/A rs7768255 79736633 + A/G rs7768001 79736672 + A/C rs7768414 79736727 + C/G rs9443633 79736782 + C/T rs9448601 79738088 + C/T rs9448602 79738107 + A/G rs4406190 79738370 + A/G rs10806154 79739086 + C/T rs12190940 79739190 + A/G rs7741943 79739286 + A/G rs9448603 79739333 + A/G rs36146106 79739418 + —/A rs9352679 79739848 + A/G rs9341756 79739909 + C/T rs9350798 79739980 + A/C rs9341757 79739993 + G/T rs7766920 79740022 + C/T rs7746653 79740031 + C/G rs7751287 79740610 + A/G rs36166556 79740631 + —/T rs36128361 79741059 + C/G rs10943610 79741136 + A/G rs9352681 79741292 + A/G rs9343857 79741450 + C/G rs9343858 79741488 + C/T rs12182951 79742891 + A/G rs12182952 79742924 + A/C rs9448604 79743377 + A/G rs9448605 79743416 + G/T rs36149780 79743416 + G/T rs4594915 79743583 + A/C rs11282710 79744026 + —/ TTCAAG CACC rs36124591 79744030 + —/ AAGCAC CTTC rs34344828 79744037 + —/ TTCAAG CAC rs7750810 79744283 + A/T rs12209235 79745085 + C/T rs34362578 79745461 + —/G rs4624830 79745780 + A/T rs1538235 79746169 + C/T rs1572584 79747009 + A/G rs34246619 79747058 + —/A rs1572585 79747295 + C/T rs10943611 79747894 + A/G rs9343859 79749118 + A/C rs11547228 79749470 − C/T rs10642979 79750856 + —/GT rs35922935 79750857 + —/GT rs35769552 79751527 + —/G rs1890229 79751748 + C/T rs1890230 79752043 + A/G rs9352682 79752074 + C/T rs35730468 79753387 + —/AAT rs4623209 79753656 + G/T rs35399714 79753801 + —/T rs12529043 79754574 + A/G rs10943612 79755099 + C/T rs35529955 79755508 + —/T rs4144107 79755536 + —/A/C rs34495466 79755537 + —/A rs3902856 79756556 + C/T rs1415862 79756757 + A/G rs1415863 79756878 + A/G rs3818839 79757044 + C/G rs34665480 79757153 + A/C rs35828088 79757480 + —/A rs9359359 79757699 + C/T rs3841156 79757786 − —/AGA rs3841155 79757996 − —/TCT rs7749615 79758494 + G/T rs6454092 79758691 + A/G rs12208915 79759454 + A/G rs9359360 79759515 + C/T rs9359361 79762302 + C/G rs35279139 79762390 + —/T rs6940637 79762564 + C/T rs6904138 79763733 + A/G rs35057263 79763873 − C/T rs41269341 79764094 + C/T rs11752126 79764642 + C/T rs7747479 79764719 + A/C rs36000864 79767181 + A/G rs9443636 79767375 + C/T rs9361477 79767525 + C/T rs13218407 79767680 + A/C rs13218727 79767681 + A/G rs9361478 79768691 + A/G rs34042644 79769661 + G/T rs2065986 79769884 + C/T rs9443637 79771427 + C/T rs13191068 79771586 + C/T rs11965967 79771803 + C/T rs9448607 79772339 + A/G rs6907674 79773483 + A/T rs35415106 79774112 + —/TTT rs9352683 79775514 + G/T rs34509958 79776185 + —/G rs9443638 79777586 + A/T rs9448608 79777881 + C/T rs1933238 79778128 + A/C rs11754374 79778672 + G/T rs7766491 79778959 + C/T rs4706747 79779358 + A/G rs4706748 79779391 + A/G rs4637600 79780227 + A/T rs9350799 79780370 + A/C rs9361479 79780474 + A/T rs35887627 79780475 + AC/TT rs9359362 79780475 + C/T rs9361480 79781148 + A/G rs34015061 79781739 + —/T rs9361481 79783469 + A/T rs36092348 79784000 − A/G rs1338023 79785047 + G/T rs9350800 79786208 + A/C rs11754419 79786367 + A/G rs9718121 79786606 + A/T rs35727754 79786754 + —/A rs1832396 79787561 − C/G rs34244224 79787746 + A/C rs34815601 79788716 + —/A rs11315927 79789321 + —/T rs9352685 79790968 + C/T rs2050659 79791088 + A/C rs2050660 79791445 + C/T rs35999901 79791481 + —/G rs28449859 79791564 + C/T rs34111968 79791750 + —/A rs9443639 79791873 + C/T rs7775074 79792805 + C/G rs34655287 79792904 + —/A rs11326550 79792916 + —/A rs7742034 79793825 + A/G rs28532298 79795101 + C/T rs35744497 79795678 + C/T rs9448609 79795708 + A/G rs3929865 79795727 + C/T rs9343860 79795729 + A/G rs3929866 79795824 + A/G rs13218541 79795927 + C/T rs3929867 79796069 + A/G rs9448610 79796341 + A/G rs6918296 79797639 + C/T rs4565265 79798677 + A/G rs2095724 79798820 + C/T rs7741282 79799097 + A/G rs35793703 79799130 + —/G rs2105143 79799666 + A/G rs1538233 79800454 + G/T rs7751422 79800799 + C/T rs35760468 79800851 + —/G rs9343861 79801587 + A/C rs10943613 79801826 + C/T rs11963444 79802291 + C/G rs34875528 79803382 + —/A rs9359363 79803610 + C/T rs9448612 79803872 + A/G rs12180022 79803813 + A/G rs9448613 79803942 + A/G rs9448614 79804316 + C/T rs4706749 79804772 + C/T rs1415861 79805047 + C/T rs5877639 79805108 + —/TTT rs4055439 79805107 − —/AAA rs35633350 79805108 + —/TTT rs34124549 79805944 + —/A rs11758432 79806313 + C/T rs6454094 79806528 + C/T rs9361482 79807104 + C/T rs35197393 79807335 + —/T rs34887019 79807963 + —/T rs9343862 79808197 + C/G rs35686657 79809315 − C/T rs9343863 79809511 + C/T rs2050662 79809792 + C/G rs9361483 79810005 + C/T rs2050663 79810113 + C/T rs7739298 79811079 + A/G rs35594811 79811779 + A/C rs9448616 79813653 + A/G rs34896515 79814085 + —/C rs13204088 79814157 + A/C rs34581263 79814707 + —/G rs34999680 79814872 + —/C rs9361484 79814937 + A/C rs9352686 79814942 + G/T rs34193659 79815383 + —/C rs28404148 79815386 + A/C rs34818907 79815757 + —/C rs9361485 79816451 + C/T rs35355402 79817319 + —/C rs4706080 79817716 + C/T rs9361486 79818479 + C/T rs2152951 79818891 + A/G rs35469490 79819211 + —/C rs9448617 79819766 + A/G rs12182597 79819707 + A/G rs11968462 79819711 + C/T rs9350801 79819985 + C/G rs9448618 79820526 + G/T rs6928507 79820970 + A/C rs6928518 79820984 + A/G rs6929315 79821334 + C/T rs9343865 79821914 + A/T rs11760038 79822663 + A/G rs34192988 79822723 + —/G rs9969106 79822922 + G/T rs6454095 79823093 + C/T rs12110918 79823270 + A/G rs9443640 79823496 + C/T rs28393972 79823721 + C/G rs28587408 79823722 + G/T rs11292616 79823758 + —/A rs6915558 79825775 + A/T rs10528595 79826027 + —/ TATATA TATATAT ATATATA rs10631256 79826038 + —/ATAT rs34479070 79826039 + —/ATAT rs10668885 79826050 + —/ ATATAT AT rs10668886 79826051 + —/ ATATAT AT/TATA TATATA rs35594282 79826052 + —/ TATATA TATA rs34850134 79826053 + —/ ATATAT ATATAT rs10943614 79826062 + A/T rs7753638 79826260 + C/T rs6917206 79826433 + C/G rs11295038 79826554 + —/A rs7454519 79827581 + C/G rs9343867 79829072 + G/T rs6925447 79829270 + C/T rs9448620 79829965 + C/G rs10688271 79832242 + —/CA rs1547731 79832823 + A/G rs9352688 79832882 + A/G rs28562383 79833897 + A/T rs9448623 79834479 + C/T rs9968921 79835098 + A/G rs34949474 79835636 + A/C rs10455120 79836486 + G/T rs12529731 79837484 + A/G rs9352689 79839533 + C/T rs9361488 79839593 + C/T rs7744876 79839756 + A/G rs9352690 79840271 + A/C rs3857447 79840542 + C/T rs28361939 79840905 + G/T rs13216433 79841107 + G/T rs9343869 79841140 + C/G rs34915363 79841523 + —/T rs9448624 79841582 + G/T rs35664126 79841883 + —/A rs9443641 79842023 + A/C rs9352691 79842326 + C/T rs34821012 79843195 + —/A rs3812161 79843364 − G/T rs12526671 79844774 + C/G rs1413967 79845731 − A/C rs9343870 79846192 + G/T rs7753531 79846715 + A/C rs1413969 79847701 − C/T rs1413968 79847761 − C/T rs4055438 79848331 + —/CACA rs1415860 79848500 − C/T rs13212056 79849331 + A/C rs7776432 79851211 + G/T rs36017295 79851212 + GC/TT rs7776138 79851212 + C/T rs1415859 79851577 − C/T rs35716913 79851705 + —/T rs12154147 79852063 + C/T rs12212124 79852485 + C/T rs9359364 79852711 + A/G rs9443642 79853322 + G/T rs9448625 79853356 + C/T rs9352693 79854791 + A/T rs9443643 79855557 + A/G rs12664690 79856551 + C/T rs9352694 79857537 + A/G rs13206256 79860401 + A/G rs11963526 79860546 + A/G rs4706750 79862281 + A/G rs7773757 79862756 + A/G rs5877640 79865118 + —/T rs35313660 79865119 + —/T rs12193154 79866583 + C/T rs7767100 79867252 + A/C rs9443644 79867363 + A/G rs7767711 79867419 + A/G rs12214911 79867844 + C/T rs4507549 79868299 + C/T rs9448627 79868502 + A/G rs6899909 79868551 + A/C rs12660124 79868563 + A/G rs28379467 79868586 + A/C rs9689135 79868589 + A/C rs9689136 79868593 + A/C rs6906253 79869724 + A/C rs34349727 79870222 + —/T rs1538232 79870555 + C/T rs7749916 79870911 + A/G rs12195753 79872084 + C/T rs34664515 79872349 + —/C rs12197385 79872695 + A/C rs11968729 79872968 + A/T rs9361489 79873504 + C/T rs4144106 79873950 + A/C rs5877641 79874047 + —/TTT rs35186945 79874048 + —/TTT rs5877642 79874056 + —/TTT rs34582407 79874057 + —/TT rs4055440 79874065 + —/T/TT/TTT rs34285696 79874066 + —/TT rs5877644 79874142 + —/A rs5877645 79874154 + —/A rs949846 79874315 − A/G rs35175594 79874354 + —/T rs6916081 79874571 + C/T rs9341758 79876533 + C/T rs9343871 79876838 + C/T rs11967829 79876870 + A/T rs4460185 79877129 + A/G rs12203969 79877616 + G/T rs35921542 79878727 + —/T rs1415310 79879033 + C/T rs34887350 79879491 + —/CA rs9443645 79879643 + C/T rs35532958 79879775 + —/G rs12208017 79880090 + G/T rs10943616 79880260 + A/G rs6940949 79880754 + A/G rs6904124 79881799 + C/G rs34131532 79882366 + —/GA rs34222053 79882584 + —/G rs9361491 79882867 + C/T rs9352696 79882949 + A/T rs34096134 79883539 + —/A rs13437410 79883867 + C/G rs1337128 79884042 + A/G rs1415311 79884599 + A/C rs9352697 79885302 + G/T rs6902186 79886779 + A/T rs6902217 79886841 + A/G rs35067617 79886856 + —/A rs34297827 79887590 + —/A rs7747226 79888212 + A/G rs7747540 79888379 + G/T rs1577793 79888739 + A/G rs34004133 79889589 + —/G rs9448636 79890158 + C/T rs9448637 79890797 + C/G rs6454096 79891729 + A/G rs7768264 79891856 + C/G rs7768535 79892231 + C/T rs11285425 79892473 + —/T rs9688601 79892482 + C/T rs11361003 79892488 + —/T rs11362933 79892493 + —/T rs12055857 79892585 + A/G rs12055858 79892634 + A/G rs9294129 79892802 + A/C rs9443647 79892908 + C/G rs34216559 79893168 + —/A rs3920791 79893453 − G/T rs1361043 79893786 − A/G rs5877646 79893802 + —/A rs1577794 79894899 − A/G rs7771746 79895912 + C/T rs7751626 79895992 + A/C rs7751628 79895996 + A/C rs7751918 79896046 + A/G rs11757274 79896170 + A/G rs1832281 79896696 − G/T rs34002011 79897278 + —/C rs9448638 79897415 + A/G rs9448639 79897548 + C/T rs36080847 79897705 + —/C rs35178487 79897768 + —/C rs9448640 79898041 + A/G rs6938269 79898250 + A/G rs34749590 79898414 + —/C rs6900032 79898558 + C/G rs6899945 79898698 + C/T rs1856089 79898889 − G/T rs1856090 79899041 − A/G rs28793115 79899460 + A/G rs6906655 79900092 + A/G rs6929531 79900136 + C/T rs2210948 79900755 − C/T rs9359366 79900866 + A/G rs9343875 79901113 + C/T rs9343876 79901219 + A/G rs9448642 79901713 + C/T rs9341760 79901973 + A/G rs9361493 79903957 + C/T rs34851468 79903998 + —/C rs2321960 79904819 + C/T rs4547969 79905337 + C/G rs2321961 79905575 + C/T rs9361496 79905887 + A/G rs6922885 79906095 + C/T rs6900076 79906130 + A/T rs34635585 79906257 + —/AA rs12527205 79906518 + C/T rs6916942 79907146 + A/G rs13192783 79907675 + G/T rs35970033 79907754 + —/GTGT rs13207216 79907776 + C/G rs9448644 79909382 + A/C rs956550 79909459 − A/G/T rs11450125 79909773 + —/A rs35277763 79909871 + —/C rs9443648 79910324 + A/G rs17785485 79910945 + C/T rs17723508 79911083 + A/G rs9448645 79911477 + A/G rs6904674 79912150 + A/C rs28369551 79912158 + A/T rs6933121 79912963 + C/T rs7768622 79913223 + G/T rs10484946 79913349 − A/G rs12196543 79914619 + A/G rs9448647 79915916 + A/T rs9352701 79916596 + A/G rs9361497 79916649 + C/T rs9448648 79916948 + A/G rs9294130 79917888 + A/G

Example 2

Further analysis of marker rs11228565, which is located within LD Block C11 and in LD with rs10896450 (D′=1, r²=0.25), was performed, with results as shown in Table 7.

Highly significant association of the A allele of rs11228565 to prostate cancer was revealed, with combined P-value for all cohorts genome-wide significant (P=6.7×10⁻¹²). The odds ratio (OR) for rs11228565 after adjusting for rs10896450 was determined to be 1.16 (P value=4.9 E-04) when using results for all populations except Finland (i.e. where we have results for both markers rs11228565 and rs10896450 in: Iceland, Chicago, Netherlands, Nashville and Spain cohorts.

TABLE 7 Association of rs11228565 with prostate cancer. Study Case Controls Control population Marker Allele P value OR Cases (n) Freq. (n) Freq. Iceland rs11228565 A 7.72E−03 1.23 1784 0.209 771 0.176 The rs11228565 A 2.15E−02 1.17 992 0.229 1781 0.202 Netherlands Spain rs11228565 A 3.42E−01 1.09 394 0.240 1399 0.224 Finland rs11228565 A 3.22E−06 1.30 2643 0.210 1689 0.169 Chicago, rs11228565 A 8.00E−02 1.16 755 0.235 878 0.210 USA Nashville, rs11228565 A 8.49E−05 1.43 592 0.291 685 0.223 USA All rs11228565 A 6.70E−12 1.23 7160 — 7203 — combined 

1. A method for determining a susceptibility to prostate cancer in a human individual, comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, or in a genotype dataset from the individual, wherein the at least one polymorphic marker is selected from rs10896450 and rs10943605, and markers in linkage disequilibrium therewith, and wherein determination of the presence of the at least one allele is indicative of a susceptibility to prostate cancer.
 2. The method of claim 1, wherein the at least one polymorphic marker in linkage disequilibrium with rs10896450 is selected from the markers set forth in Table
 5. 3. The method of claim 1, wherein the at least one polymorphic marker in linkage disequilibrium with rs10896450 is selected from the markers set forth in Table
 4. 4. The method of claim 3, wherein the at least one polymorphic marker in linkage disequilibrium with rs10896405 is selected from rs11228565 and rs7947353.
 5. A method for determining a susceptibility to colorectal cancer in a human individual, comprising determining the presence or absence of at least one allele of at least one polymorphic marker in a nucleic acid sample obtained from the individual, or in a genotype dataset from the individual, wherein the at least one polymorphic marker is selected from rs10943605 and markers in linkage disequilibrium therewith, and wherein determination of the presence of the at least one allele is indicative of a susceptibility to colorectal cancer.
 6. The method of claim 1, wherein the at least one polymorphic marker in linkage disequilibrium with rs10943605 is selected from the markers set forth in Table
 3. 7. (canceled)
 8. The method of claim 1, wherein the susceptibility is increased susceptibility.
 9. The method of claim 8, wherein the presence of the at least one allele or haplotype is indicative of increased susceptibility with a relative risk of at least 1.10.
 10. (canceled)
 11. The method of claim 8, wherein the at least one marker or haplotype comprises at least one marker selected from the group consisting of rs10896450 allele G, rs11228565 allele A, rs7947353 allele A and rs10943605 allele G. 12-17. (canceled)
 18. The method of claim 1, wherein linkage disequilibrium is characterized by values r² of greater than 0.2 and/or |D′| of greater than 0.8. 19-40. (canceled)
 41. The method of claim 1, further comprising analyzing non-genetic information to make risk assessment, diagnosis, or prognosis of the individual.
 42. The method of claim 41, wherein the non-genetic information is selected from age, gender, ethnicity, socioeconomic status, previous disease diagnosis, medical history of subject, family history of cancer, biochemical measurements, and clinical measurements.
 43. The method of claim 1, further comprising assessing the presence or absence of at least one additional genetic risk factor for prostate cancer or colorectal cancer in the individual.
 44. The method of claim 43, wherein the additional genetic risk factor for prostate cancer is selected from the group consisting of rs2710646 allele A, rs16901979 allele A, rs1447295 allele A, rs6983267 allele G, rs10896450 allele G, rs1859962 allele G, rs4430796 allele A and rs5945572 allele A.
 45. The method of claim 43, further comprising calculating overall risk. 46-67. (canceled)
 68. An apparatus for determining a genetic indicator for a cancer selected from prostate cancer and colorectal cancer in a human individual, comprising: a computer readable memory; and a routine stored on the computer readable memory; wherein the routine is adapted to be executed on a processor to analyze marker and/or haplotype information for at least one human individual with respect to at least one polymorphic marker selected from the markers set forth in Table 3 and Table 4, and markers in linkage disequilibrium therewith, and generate an output based on the marker or haplotype information, wherein the output comprises a risk measure of the at least one marker or haplotype as a genetic indicator of the cancer for the human individual.
 69. The apparatus of claim 68, wherein the routine further comprises an indicator of the frequency of at least one allele of at least one polymorphic marker or at least one haplotype in a plurality of individuals diagnosed with the cancer, and an indicator of the frequency of at the least one allele of at least one polymorphic marker or at least one haplotype in a plurality of reference individuals, and wherein a risk measure is based on a comparison of the at least one marker and/or haplotype status for the human individual to the indicator of the frequency of the at least one marker and/or haplotype information for the plurality of individuals diagnosed with the cancer.
 70. The apparatus of claim 68, wherein the at least one polymorphic marker is selected from marker rs10896450 and markers in linkage disequilibrium therewith, as defined by numerical values of r² of at least 0.2.
 71. The apparatus of claim 68, wherein the risk measure is characterized by an Odds Ratio (OR) or a Relative Risk (RR).
 72. The method of claim 5, wherein the at least one polymorphic marker in linkage disequilibrium with rs 10943605 is selected from the markers set forth in Table
 3. 